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Vienna Circle (Stanford Encyclopedia of Philosophy)

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While it is in the nature of philosophical movements and their leading doctrines to court controversy, the Vienna Circle and its philosophies did so more than most. To begin with, its members styled themselves as conceptual revolutionaries who cleared the stables of academic philosophy by showing metaphysics not simply to be false, but to be cognitively empty and meaningless.

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June 1, 2001 for Management 503 http://business.nmsu.edu/~dboje/503/

To understand Post-Scientific management, it would first be helpful to understand what Scientific Management is and thus, gain the ability to compare and contrast. I will first discuss scientific management, provide an overview of Post-Scientific management theory, compare and contrast the two methods and provide my own story. Lastly, I will attempt to deconstruct post-scientific management using resituation.

Scientific management, which was championed by Frederick Winslow Taylor (1856-1915), is based upon the theory that there is a most efficient way to do almost anything. This most efficient way must be determined by observing workers and conducting time-motion studies on their activities. This time-motion information would then be used to plan the work "scientifically" by an educated manager/leader. Workers would be paid at a higher price as an incentive to perform the work as directed. (Boje & Dennehy)

Taylor's hallmark case involved the implementation of his scientific management methods at Bethlehem Steel to move pig-iron billets, each weighing ninety pounds. This backbreaking work was done by hand. Using his methods he was able to demonstrate that he could have one employee move 47 ½ tons, per man, per day. Previously, when employees and managers had used their own individualistic methods they were only able to move approximately 12 ½ tons per man, per day. Using Taylor's method, every movement and rest break was monitored and timed by a manager to achieve improvement. The employee was essentially an automaton, the "strong back and weak mind" if you will, that followed the orders of the scientific and educated manager. (Boje & Dennehy)

While Scientific Management had its strengths and helped industry achieve some notable results, it certainly had some obvious weaknesses as well. It helped us as a society change and adapt, and theoretically facilitated society's transit down the continuum of progress. Taylor's rules for scientific management could be summarized as follows:

1. Replace rules of thumb with scientific work planning using time and motion studies, PERT (Program Evaluation and Review Technique) and Gantt charts and time tables.

2. Plan harmony in group actions, rather than discord by keeping workers in very small crews and having managers and clerks plan all work in advance, letting owners profit by savings of scientific work planning.

3. Plan cooperation of human action, rather than chaotic individualism by putting the planning job in the hands of clerks.

4. Plan maximum worker output, rather than peer-restricted output by setting worker quotas by the "best men" standards.

5. Develop all workers to the fullest extent possible for their own and their company's highest prosperity by paying people by their productivity. (Boje & Dennehy)

Post-Scientific Management was the result of a close examination of Scientific Management and the recognition that it did have serious shortcomings. The most obvious weakness was that it disregarded employees as individuals and it posited that there had to be a relationship between management and workers in order for the organization to achieve success. Mary Parker Follett was one of the first to recognize these problems.Mary Parker Follett was considerably more alert to the practical realities of relationships in organizations and their impacts on the dynamics of the whole than any of her contemporaries in management studies. She referred to the "unities" and the "co-relations" within organizations as the driving forces. Today, we call that a Systems Perspective. (Davis)

The partnership envisioned by Follett calls upon all involved in the enterprise to play a crucial role in identifying concerns and creating solutions. "We want worked out a relation between leaders and the led which will give to each the opportunity to make creative contributions to the situation" To the extent that leaders emerge during any situation, the role they must play is different than that recommended by some leadership theories. "The best leader knows how to make his (her) followers actually feel power themselves, not merely acknowledge his (her) power." Along with leadership, Follett introduces the notion of followship. "But if the followers must partake in leadership, it is also true that we must have followship on the part of leaders. There must be a partnership of following" (Davis)

Ms. Follett thought of the worker as more than just an automaton. The following summarizes some of her theories:

1. Organizations..."I have left to the last what seems to me the chief function , the real service, of business: to give an opportunity for individual development through the better organization of human relationships."

2. Leadership..."The Leader is the one who can organize the experience of the group...and thus get the full power of the group. The leader makes the team...Men with this ability create group power rather than express a personal power."

3. Power..."You can not coordinate purpose without developing purpose, it is part of the same process. Some people want to give the workmen a share in carrying out the purpose of the plant and do not see that that involves a share in creating the purpose of the plant."

4. Coordination... "Collective responsibility is not something you get by adding up one by one all the responsibilities. Collective responsibility is not a matter of adding but interweaving, a matter of reciprocal modification brought about by the interweaving."

5. Conflict... "Thus we shall not be afraid of conflict, but shall recognize that there is a destructive way of dealing with such moments and a constructive way. Conflict as the moment of the appearing and focusing of difference (emphasis added) may be a sign of health, a prophesy of progress."

6. Management... "And that is always our problem, not how to get control of people, but how all together we can gain control of a situation." (Horne)

Both theories emphasize the importance of planning in the work process, however, there aren't many similarities once you get past that point. In the interest of brevity, I'll point out some of the contrasting elements or dualities of the Scientific Method and the Post-Scientific Method.

Leader & Worker development

I would be remiss if I did not mention Foyal in this discussion. I see Henri Fayol as a key player in attempting to bridge the gap between these two theories. He contended that management needed knowledge of a more diverse set of disciplines then merely mathematics and engineering in order to be good planners and controllers of tasks. He also believed that workers required greater knowledge as well. However, his emphasis seemed to be more upon managers than workers. (Boje & Dennehy)

In my own experience of Post-Scientific management, as an eighteen year old, I needed money and so took a job in a copper mine in Bagdad, Arizona. This was indeed backbreaking work that required me to do a certain amount of work, i.e., move a certain amount of dirt and gravel using sledge-hammers and shovels, in the course of a ten hour day, and I had to keep up with the schedule of blasting. However, I had some latitude as to how I could do it. Far from being a team-management activity, I did have to communicate with my boss, who had been in the business for almost fifteen years, regarding structurally weakened areas. Since I knew almost nothing about geology, the last thing the corporation wanted was a cave-in.My boss did most of the planning and directed most of my moves, but he did need some input from me and the others that worked for him to improve efficiency.Or, phrased another way, avoid calamities that would slow down progress and cost the company huge sums in wrongful death lawsuits.

To resituate is to rewrite the story in order to observe another viewpoint such as those that are marginalized or excluded. Since these theories emphasize the manager-worker duality, the relationship-individual duality, and when considering Follett and Taylor, the male-female duality there are several ways to rewrite the story. I believe the sweatshop example provides a good setting to re-tell the Post-Scientific story, since it involves all of these dualities. Post-Scientific Management doesn't go far enough, in my opinion, to include the talents and skills of the worker. In sweatshops around the world, owners should strive for a greater balance in the hiring of men and women, decrease the dependence on scientific management, and seek to improve relationships between workers and managers, while increasing wages. Currently, workers are the marginalized voices in this industry and sweatshops are becoming social pariahs. Increasing worker knowledge, improving inter-relationships, and asking employees for input, at least in the post-modern sense, should help to eliminate many of the centers. (Boje)

In a sort of "Men are from Mars and Women are from Venus" look at the resituation, would it matter if Mary Follett had been a man? Would her observations regarding the "softer" skills of personal relationships been taken more seriously? Are women more tuned-in to the importance of relationships than men? Without stereo-typing, I'm convinced that that there are differences in male-female observations, and these differences must be recognized with the understanding that one is just as viable as the other.
References used:
Boje & Dennehy, "Manageing in the Post Modern World." Chapter 2 http://business.nmsu.edu/~dboje/mpwchap2.html

Albie M. Davis, "Liquid Leadership: The Wisdom of Mary Parker Follett (1868-1993)"

John F. Horne III, "Mary Parker Follett: Visionary Genius Finds her Own Time"

David Boje, http://cbae.nmsu.edu/~boje/503
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June 1, 2001 for Management 503 http://business.nmsu.edu/~dboje/503/ To understand Post-Scientific management, it would first be helpful to understand what Scientific Management is and thus, gain the ability to compare and contrast. I will first discuss scientific management, provide an overview of Post-Scientific management theory, compare and contrast the two methods and provide my own story.

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Resource #2

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As every manager knows, new technologies are transforming products, markets, business processes, and entire industries, revolutionizing the business environment. Yet the more technology looms as a factor of competition, the more the emphasis in managerial books, executive education classes, and corporate training seminars is on the "soft" arts of leadership, change management, and employee motivation. In other words, the more science and technology reshape the very essence of business, the less useful the concept of management itself as a science seems to be.

On reflection, this paradox isn't so surprising. The traditional scientific approach to management promised to provide managers with the capacity to analyze, predict, and control the behavior of the complex organizations they led. But the world most managers currently inhabit often appears to be unpredictable, uncertain, and even uncontrollable.

Not so long ago, for example, Compaq Computer was everybody's model of a lean, dynamic start-up that could successfully do battle with sluggish giant IBM. But that was before mail-order clone-makers like Dell and Northgate arrived on the scene. Now yesterday's start-up is today's sluggish giant, and Compaq faces the painful task of recreating itself in a radically changed competitive environment.

In the face of this more dynamic and volatile business world, the traditional mechanisms of "scientific management" seem not only less useful but positively counterproductive. And science itself appears less and less relevant to the practical concerns of managers.

However, the problem may lie less in the shortcomings of a scientific approach to management than in managers' understanding of science. What most managers think of as scientific management is based on a conception of science that few current scientists would defend. What's more, just as managers have become preoccupied with the volatility of the business environment, scientists have also become preoccupied with the inherent volatility of nature and with the dynamics of unpredictable and unstable systems in the natural world.

Put simply, while traditional science focused on analysis, prediction, and control, the new science emphasizes chaos and complexity. Today scientists are developing powerful descriptions of the ways complex systems-from swarms of mosquitoes to computer programs to futures traders in commodities markets-cope effectively with uncertainty and rapid change.

And therein lies an opportunity for fruitful dialogue between the world of management and the world of science. The new rules of complex behavior that cutting-edge scientific research describes have intriguing parallels with the organizational behaviors many companies are trying to encourage. Science, long esteemed by business as a source of technological innovation, may ultimately prove of greatest value to managers as a source for something else: useful new ways of looking at the world.

The wide-ranging texts reviewed here suggest the broad outlines of what might become the new scientific management. Their message: management may indeed be a science-but not the science that most managers think.

The Science Behind Scientific Management

To understand the implications of the new science for management, start with the book that coined the term "scientific management." In 1911, the turn-of-the-century industrial engineer Frederick Winslow Taylor published his magnum opus, The Principles of Scientific Management, which laid out his ground rules for efficient industrial organization. Taylor's book is now a classic of managerial literature. His ideas have shaped companies across the industrial spectrum and defined the task of management for generations of managers.

The Principles of Scientific Management, Frederick Winslow Taylor (New York: Harper, 1911).

Chaos: Making a New Science, James Gleick (New York: Viking, 1987).

Complexity: Life at the Edge of Chaos, M. Mitchell Waldrop (New York: Simon & Schuster, 1992).

The Fifth Discipline: The Art and Practice of the Learning Organization, Peter M. Senge (New York: Doubleday, 1990).

Taylor's book was profoundly influenced by the concerns of the science-particularly the physics-of his time. In the nineteenth century, Newton's laws of motion were first used to analyze the forces exerted on and by complex physical systems, allowing scientists to predict the behavior of those systems. Meanwhile, the principles of thermodynamics, elucidated in the second half of the nineteenth century, provided the one missing ingredient-heat interactions-needed to complete Newton's conception of the physical world. Together these theories allowed scientists to calculate how machines could function with maximum efficiency.

From the opening pages of his book, Taylor was preoccupied with the problem of efficiency as it applies to organizations. When it comes to natural resources, he argued, people clearly understand the need for efficiency because "we can see and feel the waste of material things." But "our larger wastes of human effort," brought on by the "awkward, inefficient, or ill-directed movements of men," are "less visible, less tangible, and...but vaguely appreciated."

According to Taylor, the fundamental cause of this waste of human effort was unscientific management. In other words, he thought managers focused too much on the output of work and not enough on the processes by which the work was done. In most turn-of-the-century workplaces, managers paid workers for predetermined outputs, usually through some type of "piecework" system, then left it to work crews to determine the actual methods of the work. Taylor disparaged this approach, calling it the "initiative and incentive" system. "It is only by giving a special inducement or 'incentive'...that the employer can hope even approximately to get the 'initiative' of his workmen."

It's ironic to read Taylor's criticisms today, when so much emphasis has been placed on encouraging employee initiative on the job and on crafting incentive systems that "pay for performance." Still, there were good reasons for why Taylor saw "initiative" and "incentive" as part of the problem rather than part of the solution. As long as the managers of his day depended on work groups to decide how work was done, they had no way to directly influence the efficiency of the organization. Indeed, traditional management was an inherently unstable system, which forced managers either to rely on coercion or to abdicate their authority altogether. For example, one common way managers tried to boost productivity was by regularly raising piece rates once most workers met them. But this only induced workers to engage in "soldiering"-that is, to limit their output intentionally in order not to undermine established rates.

Taylor's solution was "the substitution of a science for the individual judgment of the workman." Managers were to separate the planning of work from its actual execution and reserve for themselves the choice of methods by which a particular task was done. By analyzing all of the steps in a work process and creating standardized procedures for each step, managers could identify the "one best method" for performing a task that would guarantee maximum efficiency. "The best management is a true science," Taylor wrote, "resting upon clearly defined laws, rules, and principles as a foundation." And those laws constituted an understandable, predictable, controllable system. "In the past the man has been first; in the future the system must be first."

In effect, Taylor urged the individual manager to think of himself as a scientist who alone understands the fundamental laws of the system he is studying. For Taylor, the worker played a passive role, almost as if he were part of the apparatus of the experiment. Over and over again in his book, Taylor repeated this "general principle": No matter what the job or how seemingly simple the task, "the science which underlies each workman's act is so great and amounts to so much that the workman who is best suited actually to do the work is incapable (either through lack of education or through insufficient mental capacity) to understand the science." It is only the manager, armed with a scientific predisposition to "search for general laws or rules," who can understand the true science of work.

But this is not to say that Taylor ignored the issue of employee motivation or the psychological dimension of work. On the contrary, a major part of The Principles of Scientific Management concerns "the accurate study of the motives which influence men." That is, for scientific management to be successful on Taylor's terms, managers must do more than just analyze and reorganize work. They need to effect "a complete revolution in the mental attitude" of the worker.

Yet even here Taylor reflected the scientific assumptions of his day-particularly the belief that "the motives which influence men" can be reduced through scientific analysis and control in the same way that the physical activities of shoveling iron or cutting metal can be. In discussing employee motivation, Taylor noted, "At first, it may appear that this is a matter for individual observation and judgment and is not a proper subject for exact scientific experiments." But while psychological laws are more complicated and subject to exceptions, "owing to the fact that a very complex organism-the human being-is being experimented with," Taylor maintained that "laws of this kind, which apply to a large majority of men, unquestionably exist and when clearly defined are of great value as a guide in dealing with men."

After such lofty language, some of Taylor's actual suggestions are self-evident. For example, he insisted that productivity improvements based on scientific management be shared with workers in higher wages; otherwise they won't cooperate in work reorganization. Other suggestions of his are crude and simplistic, like this major piece of advice: Never deal with workers as a group, only deal with one individual at a time. "When men work in gangs, their individual efficiency falls almost invariably down to or below the level of the worst man in the gang." Taylor's solution was to have workers assigned individual tasks that they were to perform in the greatest possible isolation.

But whatever one thinks of his specific suggestions, they all share the nineteenth-century scientific regard for reductionism: breaking down things into isolated parts in order to better control them. Indeed, all of the techniques of scientific management-the planning department, time-and-motion study, standardization of methods and tools, and the like-are so many means to this end. But Taylor urged his readers not to confuse the techniques with the basic scientific principles. "It is only through enforced standardization of methods, enforced adoption of the best implements and working conditions, and enforced cooperation that this faster work can be assured. And the duty of enforcing the adoption of standards and enforcing this cooperation rests with the management alone."

Frederick Taylor's principles inaugurated a revolution in management and in the organization of work. In the decades after his book's publication, Taylor's ideas contributed to massive increases in productivity and the standard of living. However, the experience of the last 20 years has taught managers that in a new business environment such "scientific" principles are a recipe for disaster. In fast-changing markets, the fragmentation of work, the separation of planning from execution, and the isolation of workers from each other create rigid organizations that can't adapt quickly to change. As a result, managers must now rethink the fundamental elements of Taylor's system: work organization, employee motivation, and the task of management.

The majority of new managerial ideas-like cross-functional teams, self-managed work groups, and the networked organization-are either direct or indirect responses to the inadequacies of Taylor's original model. Yet for all of the proliferation of specific techniques, the fundamental principles of a new managerial paradigm are far from clear.

At this current crossroads, recent developments in science may prove helpful. Even as Taylor was codifying his own organizational system, scientists were beginning to understand the shortcomings of the nineteenth-century scientific models on which that system was based. Within a decade of the publication of Taylor's book, new developments in physics-Einstein's relativity theory and quantum mechanics-suggested that at the extremes of space and time, from the universe in its entirety to subatomic particles, the laws of Newtonian physics broke down. And more recently, scientists have extended that message of uncertainty and unpredictability to the everyday world.

Coping with Chaos and Complexity

Nineteenth-century physics, based on Newton's laws of motion, posited a neat correspondence between cause and effect. Scientists were confident that they could reduce even the most complex behaviors to the interactions of a few simple laws and then calculate the exact behavior of any physical system far into the future. This conviction profoundly shaped Taylor's analysis of organizations and of that "very complex organism," the human being at work. But during the past few decades, more and more scientists have concluded that this and many other of science's traditional assumptions about the way nature operates are fundamentally wrong. Far from being as predictable as clock-work, nature appears as random as a throw of the dice.

"Chaos theory" is the general term for this new model of how things work, and probably the best introduction to it is the best-selling book Chaos by science writer James Gleick. According to Gleick, the chief catalyst for chaos theory was the research of MIT meteorological scientist Edward Lorenz. In the early 1960s, Lorenz developed a computer program that simulated a weather system. By plugging in numbers representing the initial state of winds and temperatures, Lorenz's program churned out the subsequent weather pattern as it evolved over time. Lorenz, like most scientists, assumed that small changes in the initial conditions he fed into the computer would result in correspondingly small changes in the evolution of the entire system. To his surprise, he discovered that even the most minuscule of changes caused drastic alterations in the weather pattern. In effect, a slight breeze in Idaho or a one-degree drop in temperature in Massachusetts could end up changing balmy weather in Florida into a hurricane a month later.

The effect defied both intuition and what meteorologists had previously understood about their science. Intrigued by Lorenz's puzzle, scientists from a wide variety of fields began experimenting with simulations of other physical systems, only to discover the identical phenomenon. An infinitesimal change in initial conditions could have a profound effect on the evolution of the entire system. Take the simple example of water dripping from a faucet. Speed up the rate of flow ever so slightly, and the pattern by which drops fall changes radically. Repeat the experiment again, and the pattern will be completely different. What's more, the pattern of drip formation changes in ways that no one can model. Even the most powerful supercomputer can't predict when the next drip will fall.

What is true for the weather and a dripping faucet has proved equally true for the vast majority of physical systems. A slight shift in temperature causes sudden turbulence in a pan of water. A tiny accumulation of charge triggers a lightning bolt. A small shift in the fertility rate doubles the population of a community of gypsy moths.

This basic insight-that minute changes can lead to radical deviations in the behavior of a natural system-has inaugurated an equally radical shift in how scientists see the world. Put simply, the nineteenth-century emphasis on predictability and control has given way to a late twentieth-century appreciation for the power of randomness and chance. For all practical purposes, the behavior of even relatively simple physical systems is fundamentally unpredictable.

But this is not to say that chaotic systems don't have any patterns. While the idea that nature is fundamentally random is counterintuitive, chaos theory's second basic insight is even more so: that patterns do lurk beneath the seemingly random behavior of these systems. In fact, systems don't end up just anywhere; certain paths apparently make more sense-or at least occur much more frequently-and chaos theorists call such paths "strange attractors." Thus while meteorologists can't say with certainty what the weather will be on a particular day in the future, they can estimate the probability of the kind of weather likely to occur. In other words, strange attractors allow scientists to determine within broad statistical parameters what a system is likely to do-but never exactly when a system is likely to do it. The cause-and-effect precision of traditional physics has been replaced by the statistical estimate of probabilities.

In addition, the way scientists identify the predictable patterns in a system has been turned on its head. Instead of trying to break down a system into its component parts and analyze the behaviors of those parts independently-the reductionist tradition that so influenced Taylor-many scientists have had to learn a more holistic approach. They focus increasingly on the dynamics of the overall system. Rather than attempting to explain how order is designed into the parts of a system, they now emphasize how order emerges from the interaction of those parts as a whole.

The quest to gain insight into and make use of the order that emerges from chaotic systems is the subject of Complexity, M. Mitchell Waldrop's upcoming book. Waldrop, a contributing correspondent of Science magazine, describes some recent research from the Santa Fe Institute, a New Mexico think tank specializing in the analysis of "self-organizing" systems. The institute has brought together an eclectic group of scientists who focus on the ways that the simple actions of independent components can combine to produce extremely complex behaviors, even in the absence of any central intelligence or control. Santa Fe chemists, for example, are examining how molecules organize themselves into self-reproducing proteins. Biologists are determining how cells arrange themselves into immune systems. And economists are considering how the limited actions of individual buyers and sellers form complex markets, industries, and economies.

In the process, the Santa Fe researchers have developed some basic rules for what Waldrop calls "complex adaptive systems." These systems, Waldrop claims, are among the most successful in nature. Some examples include the ecology of tropical rain forests, colonies of ants, and even the human brain.

Such systems have several characteristics in common. First, they are "self-managed"-that is, they consist of a network of "agents" that act independently of one another and without guidance from any central control. For example, each one of the brain's roughly 100 billion neurons is a kind of miniature chemical computer that follows its own independent pattern of behavior. Take a neuron out of the brain, and it can still function. There is no "master neuron" or central area of the brain that controls what each neuron does.

Yet these agents are capable of engaging in cooperative behavior. They can form groups or "communities" that cooperate in producing higher-order behaviors that no single agent could accomplish on its own. In the brain, each neuron is connected to millions of others. Some communities of neurons, clustered in particular areas of the brain, specialize in functions such as language or visual recognition. It is precisely the interactions among neurons that produce human intelligence. For example, the structural difference between individual squid neurons and human neurons is relatively small. However, a human brain not only contains many more neurons than a squid's but also the organization of its neurons is much more complex and interwoven.

A particular kind of feedback makes self-management possible. In a sense, self-organizing systems are learning systems but of a specific sort. Capable of "learning" through feedback from the external environment, they also "embed" that learning in their actual structure. For instance, the more a set of neurons is involved in some piece of mental work-like recognizing a face or solving a mathematical problem-the stronger the actual chemical connection among the neurons (and the easier for the brain to make the connection the next time). Indeed, the human brain is forever reconfiguring the connections between neurons in response to external and internal stimuli. In this way, self-organizing systems constantly rearrange themselves as the effects of previous actions or changes in external conditions ripple through the system. Information is embedded in structure. As external conditions change, the structure of the system automatically changes.

Finally, self-management and learning through feedback allow these systems to operate by "flexible specialization." Self-organizing systems usually contain an array of specialized behavioral niches occupied by specific agents or groups of agents. However, old niches constantly disappear and new ones are created as the external environment changes. Therefore, agents aren't permanently locked into previously useful behaviors that have since become obsolete, which helps the system as a whole adapt to change. Waldrop notes that self-organizing systems tend to change so rapidly and so completely that it becomes meaningless to talk about agents or groups of agents "optimizing" (a term redolent of the nineteenth-century focus on efficiency) their behavior. Rather, such systems are characterized by what Waldrop calls "perpetual novelty."

In general, the complex adaptive systems found in nature contain individual agents that network to create self-managed but highly organized behavior; respond to feedback from the environment and adjust their behavior accordingly; learn from experience and embed that learning in the very structure of the system; and reap the advantages of specialization without getting stuck in rigidity. If these characteristics sound familiar, it's because they so closely match the new kind of organization many managers are struggling to create in order to cope with a more uncertain-and frequently chaotic-business environment.

According to Waldrop, few complexity researchers have applied the concepts of their emerging field to the specific organizational problems managers face. But one area of research at the Santa Fe Institute takes a step in that direction. Economists at the institute are creating computer simulations of economic transactions much as Lorenz simulated weather systems some 30 years ago. Their goal is to model complex market behaviors by constructing them from the interaction of a limited set of simple building blocks. "Instead of viewing the economy as some kind of Newtonian machine," writes Waldrop, "they would see it as something organic, adaptive, surprising, and alive."

Simulating economic behavior isn't easy. Although programmers need only model the simple behaviors of individual agents and then let self-organization do the rest, it's not always clear which simple behaviors will result in a simulation that accurately reflects reality. So far, the Santa Fe researchers haven't come up with a convincing computer version of an entire economy. They have, however, developed simulations that represent limited aspects of economic activity, and some of these simulations have produced quite realistic behaviors.

One program, for example, simulates the stock market. It consists of agents that decide when to buy or sell stock. As in real stock markets, the actions of the computerized "traders" determine the price of the stock. At first traders made decisions randomly; but soon they came to buy and sell stock exactly as classical economic theory says they should-according to the stock's fundamental value as set by its discount rate and dividend. Still later in the simulation, the agents "discovered" that by studying the history of a stock's price performance, they could make money by bidding a stock above and below its actual value. The result: the computer system learned to simulate the same kinds of bubbles and crashes that occur in real markets. Much as chaos theory has revealed the shortcomings of traditional physicists' mathematical models of the world, these simulations have pointed up the shortcomings of the elegant mathematical models of neoclassical economists.

For the Santa Fe researchers, the stock market simulation is just a start. They believe that if they can accurately simulate an entire economy, the computer system could be used, in the words of one scientist quoted by Waldrop, as a "flight simulator" for economic decision making. Such a program could estimate the probability of boom and bust cycles, simulate the effect of various government policies, or indicate what changes in consumer or business behavior might lead to more vital economies. In the meantime, one leading Santa Fe researcher has founded the Prediction Company, a commodities trading company that will make investment decisions with the help of a computerized trading simulator.

Toward a New Managerial Science

Chaos theorists and complexity scientists may not be studying business organizations, but their perspective has already shaped recent managerial literature. For an example, consider one of the most popular managerial books of the last few years, The Fifth Discipline by MIT researcher Peter Senge.

If Taylor's chief concern was inefficiency and waste, then Senge's is chaos and complexity-and the loss of purpose that frequently comes in their wake. Most people, Senge argues, feel lost in the organizations of which they are a part. Managers are overwhelmed by too much information, too many rapid changes, and too many conflicting demands. "When asked what they do for a living," Senge writes, "most people describe the tasks they perform every day, not the purpose of the greater enterprise in which they take part. Most see themselves within a 'system' over which they have little or no influence. They 'do their job,' put in their time, and try to cope with the forces outside of their control."

According to Senge, this systematic inability to cope with complexity is a direct result of traditional scientific approaches to management. From its opening sentences, The Fifth Discipline is an attack on the reductionism at the center of both Taylor's system and all of nineteenth-century science. "From a very early age," Senge notes, "we are taught to break apart problems, to fragment the world. This apparently makes complex tasks and subjects more manageable, but we pay a hidden, enormous price. We can no longer see the consequences of our actions; we lose our intrinsic sense of connection to a larger whole."

In a sense, managers are in a position rather similar to that of pre-chaos natural scientists. They think they understand the relationships between cause and effect in their organizations. But in fact, the links between actions and results are infinitely more complicated than most managers suspect. Senge calls this the "core learning dilemma" in organizations today: "We learn best from experience, but we never directly experience the consequences of many of our most important decisions."

As a result, managers are prisoners of the very systems they are supposed to manage. They understand neither the underlying dynamics of these systems nor how to influence those dynamics to achieve organizational goals. Indeed, the idea of the manager as an omniscient scientific planner is fundamentally misguided. According to Senge, "The perception that someone 'up there' is in control is based on an illusion-the illusion that anyone could master the dynamic and detailed complexity of an organization from the top."

The alternative is to stop seeing an organization as a machine-Taylor's mistake-and to begin viewing it as a kind of living organism. This requires a holistic approach that reflects chaos theory's focus on the overall behavior of a system. "Living systems have integrity," Senge writes. "Their character depends on the whole. The same is true for organizations; to understand the most challenging managerial issues requires seeing the whole system that generates the issues."

"Systems thinking" is the fifth discipline of Senge's title. As he portrays it, systems thinking is the ability to understand the key interrelationships that influence behavior in complex systems over time-and should give managers the capacity for "seeing wholes."

Consider Senge's story of a high-tech start-up from the 1960s, a case based on a number of real instances. After a few years of blistering growth, the company he calls WonderTech experienced a sudden drop-off in sales. Desperate to sustain growth, senior managers hired more salespeople and aggressively pushed marketing. These actions did increase sales as intended but only for awhile. WonderTech entered a period of volatile swings between high and low demand that eventually forced it into bankruptcy.

In this case study, Senge traces the source of WonderTech's failure to management's ignorance of a few basic feedback processes. Put simply, high demand increased pressure on the company's production capacity. Inadequate capacity meant large backlogs of orders and long delays in delivery. Customers became angry and dissatisfied, which caused sales to drop.

As Senge tells the story, senior managers did understand that as sales grew, the company needed to invest in capacity. But as their fixed investments in manufacturing increased, so did their need to keep sales up and their tendency to push sales and marketing to get more orders. Because the two sides of the organizational system-sales and manufacturing-were never in balance, the vicious circle of high growth, undercapacity, delayed delivery, and customer dissatisfaction repeated itself over and over again, continually growing worse.

Senge notes that there are a limited number of such feedback processes at work in any organization, what he calls "systems archetypes." In a sense, they are the organizational equivalents of strange attractors in chaos theory: the basic patterns of behavior that occur in all organizations again and again.

The WonderTech story illustrates a number of these archetypes. Senge's term for one of them is "limits to growth"-the idea that any growth process produces the conditions for its own collapse. The more WonderTech focused on sales, the more it created a capacity problem that retarded sales. Senge calls another "shifting the burden"-the idea that a short-term solution to a problem may actually make it worse by undermining an organization's ability to implement a more fundamental, long-term solution. Managers at WonderTech became so preoccupied with boosting sales that they were never able to focus on the real solution to their problem: expanding production capacity to control delivery time.

For Senge, it is precisely the systemic, automatic quality of these processes that accounts for the "out of control" feeling so many managers experience. Ignorant of the systems archetypes, they end up always seeing only the part, never the whole. In contemporary organizations, he argues, it is the work of managers-and, indeed, everyone-to understand the systemic processes driving human behavior and to change them: "The art of systems thinking lies in seeing through complexity to the underlying structures generating change."

When managers understand the dynamics of these archetypes and are able to make the deep connections between systems and behavior, they are in a position to effect real change. And just as chaos theory teaches that small changes can have big effects in physical systems, a crucial concept in systems theory is "leverage": the idea that "small, well-focused actions can sometimes produce significant, enduring improvements." In the WonderTech case, a simple commitment to rapid delivery-a strategy managerial experts have since enshrined in the rubric "competing on time"-would have done more to solve the company's problems than all the salespeople in the world.

If managers master systems thinking and the other disciplines Senge describes, the result is "the learning organization." As Senge portrays it, this learning organization has characteristics remarkably similar to the complex adaptive systems that scientists are discovering in nature. It is a highly decentralized system in which any number of decision-making processes on the local level maintain order throughout and constantly adjust to change.

In effect, Senge's disciplines are meant to replicate in human organizations the organic control found in nature. One of the most interesting discussions in his book concerns the tools that some organizations are creating to help managers develop the skills they need to make organic control work. Take the example of microworlds, which are computer-based simulations of complex business situations based on the principles of systems thinking. With microworlds, managers can experiment with their organizations to reveal the largely hidden dynamics of complex systems, much as scientists use simulations of the weather or water dripping from a faucet to learn how physical systems work.

At MIT's Sloan School, for example, first-year business students use a microworld simulating the rise and fall of People Express airline. With it, they explore the interrelated forces that, over a six-year period, caused People Express to lurch from one of the fastest growth rates in airline industry history to a sudden financial crisis and eventual purchase by a competitor. At the Hanover Insurance Company, managers train in a "claims learning laboratory" with microworlds that simulate the processes by which adjusters settle claims in the insurance industry. By allowing users to try out alternative approaches to solving business problems, such systems help managers to deepen their understanding of the systems of which they are a part. Microworlds also allow managers to recognize those strange attractors that may underlie behavior in all organizations and thus to identify high-leverage strategies for change.

As the language of "experiments" and "laboratories" suggests, Senge's new manager is every bit as much a scientist as Taylor's was-but, of course, a scientist of a very different sort. As Senge puts it, the scientific managers of today must be researchers who study their own organizations. And they must be designers who create the learning processes that make self-organization possible, the processes that are essential to effective performance in a world characterized by perpetual novelty and change.

A version of this article appeared in the November-December 1992 issue of Harvard Business Review.

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As every manager knows, new technologies are transforming products, markets, business processes, and entire industries, revolutionizing the business environment. Yet the more technology looms as a factor of competition, the more the emphasis in managerial books, executive education classes, and corporate training seminars is on the "soft" arts of leadership, change management, and employee motivation.

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The "Scientific Management" movement was born in early twentieth-century Philadelphia factories but spread rapidly, transforming not only management techniques but also popular conceptions of industrialized society itself. According to its founders, the system simply sought the "one best way" to perform any task. But its time-study engineers, along with the assembly line, came to symbolize the bleak and mechanical organization of workers' lives by industrial engineers. Its advocates, on the other hand, hailed scientific management as the basis for the transformative increases in productivity that, they argued, improved the lives of working people.

Although many early management consultants contributed to the development of the system, Philadelphia's Frederick Winslow Taylor (1856-1915) is acknowledged as the "Father of Scientific Management"; in fact, the system is also known as "Taylorism." His concepts and practices were embraced by industrialists and municipal reformers, attracted devoted followers and harsh critics, and inspired, if indirectly, numerous movements seeking to reorganize society by making it more efficient. The first incubators of Taylor's experiments were Philadelphia factories, and by the mid-twentieth century his associates and imitators had installed "scientific" systems of management in all kinds of establishments throughout the region and, from there, the world. By the twenty-first century, timed-to-the-second fast-food and help-desk workers were so commonplace that most Americans did not realize how Taylorized their workplaces had become.

According to its proponents, scientific management sought the "one best way" to perform any task. Applied to manufacturing, and later to other fields, it meant that "waste" of any kind, especially waste of time, must be eliminated, resulting in vastly improved productivity. Whereas earlier manufacturing relied on the expert knowledge and decision-making of craftsmen, the new approach attempted to transfer all knowledge of the manufacturing process to management-and in particular to new planning departments-which would then instruct workmen on the precise methods and motions to be used to perform each job.

The "Efficiency Craze"

The system's implementation, in companies as varied as the Link-Belt Engineering Company at Hunting Park Avenue and Twenty-First Street in Nicetown, Cramp Shipyard in Port Richmond, and Bethlehem Steel in South Bethlehem, Pennsylvania, was often beset with problems and sometimes ultimately rejected. Yet the "efficiency craze" that Taylor launched spawned numerous management consulting firms as well as do-it-yourself efforts at many companies. His arguments also convinced corporate management that it must control all aspects of how work is done if it was to survive in the cutthroat competitive world of twentieth-century capitalism. Not unexpectedly, unions like the International Association of Machinists fought these new management schemes in order to defend their members' prerogatives and union work rules, and in other cases to oppose "speedup" or at least gain a larger share of the increased proceeds from greater productivity.

Despite the global spread of scientific management, its origins and first several decades were a thoroughly Philadelphia story. Frederick Winslow Taylor was born in 1856 in Germantown to an old Quaker family. He spent his youth attending Germantown Academy, touring Europe, and engaging in cricket with friends from similarly wealthy families, though he never matriculated at Harvard as expected. Perhaps surprisingly, he used family connections to instead begin an apprenticeship as a patternmaker and machinist at the Enterprise Hydraulic Works, a pump manufacturer at Twenty-Second and Race Streets. The Industrial Revolution was reshaping not only the American economy by the 1870s but also society itself, and Philadelphia was at its lead, rapidly becoming the " Workshop of the World." It was not unusual for some young men from wealthy families to use the route of apprenticeship to gain the knowledge they needed to advance in industry.

After he completed his apprenticeship at Enterprise, Taylor began working at Midvale Steel in Nicetown. Once again he tapped family connections, for Midvale was owned by the father of Taylor's tennis partner and by Taylor's future brother-in-law. He started at the bottom, working as a laborer for a few weeks to learn how jobs were done and to attempt to understand the motivations of workers. Taylor moved up quickly, eventually becoming chief engineer of the works, and it was in the course of his employment there that he developed the prototypes for the innovations he would become famous for.

Although Taylor is most remembered for his management and organizational ideas, he also made contributions to mechanical processes and machinery, designing a giant steam hammer at Midvale, developing "high-speed steel" at Bethlehem Steel, and earning 42 patents. In fact, he first used a stopwatch to gauge the performance of machine tools, but he soon applied the same techniques to measure the motions of human workers. As Taylor formulated and refined his approach to scientific management at a succession of companies in the Philadelphia region from the late 1870s to the early 1900s, he increasingly regarded workers as elements of the production process. In his view, their actions could be precisely molded, with the right incentive schemes, by a new type of management that left no leeway for personal discretion.

"Schmidt" the Achiever

In Taylor's most well known, if partially fabricated, description of his techniques, he claimed to have turned an average laborer at Bethlehem Steel he called "Schmidt" (actually named Henry Noll [1871-1925]) into a superhuman loader of pig iron (although he "firmly believe[d] that it would be possible to train an intelligent gorilla so as to become a more efficient pig-iron handler than any man can be"). Revealing his own class attitudes towards laborers, Taylor related, in his lectures and writings, what he thought of Schmidt, a "man so stupid that he was unfitted to do most kinds of laboring work," though he built his own house, was married, and had a grade-school education.

Although Schmidt was purportedly happy with the deal, other workers at Bethlehem and elsewhere were not. Taylor claimed that he did not oppose unions, but he believed they would be an unnecessary encumbrance in a scientifically managed company, where increased wages for greater output would make everyone richer-and happier. Consequently, he urged companies like Link-Belt to keep unions out and was disappointed when they ignored his advice. The experience of scientifically managed companies in regard to organized labor was checkered. Taylor proudly noted that workers at companies for which he consulted, such as Link-Belt and Tabor Manufacturing, did not participate in Philadelphia's massive general strike in 1910. But he did not mention the long and bitter strike that same year that targeted the bonus system at Bethlehem Steel, one of the remnants of Taylor's earlier efforts there. The resentment expressed by one employee of a Philadelphia manufacturer for the "silk-shirted bespectacled slide rule and stopwatch expert" who watched and timed his actions was not uncommon. Labor opposition to "speedup" systems grew rapidly, and Bethlehem workers even gave the system's founder a new moniker: "Speedy Taylor."

Unionists were not the only opponents of scientific management, however. Philadelphia companies like Baldwin Locomotive relied heavily on the expert skill and knowledge of their craftsmen and had no interest in Taylor's ideas. Others, like Cramp Shipyard and Bethlehem Steel, experimented extensively with the new approach but eventually rejected it, claiming it was expensive and highly disruptive. Yet even those companies kept some parts of the system in place: Bethlehem simply renamed Taylor's "instruction cards" to "speed cards." Cramp's management rejected his recommendation to "speed . . . up all of the machinery in your shops 60% beyond its present speed," but kept his better-organized tool room. Some avid enthusiasts, like Oberlin Smith (1840-1926) of Bridgeton, New Jersey's Ferracute Machinery Company, wanted to install the system, but Smith was "appalled" at the estimated expense to implement it in 1907, though he finally implemented a similar program some years later.

Workers and socialists attacked Taylor's version of scientific management for turning workers into automatons, deskilling craftsmen, and firing those who could not or would not perform as "first-class men." Yet, if managers strictly followed Taylor's prescriptions, the workers who remained did at least see pay increases, and piece rates were not reduced (at least initially). But after Taylor withdrew from active consulting in 1901, his disciples and followers, and soon other "consultants" who saw an opportunity to cash in on the latest management fad, were often less scrupulous about how the returns from increased productivity should be shared.

The Spread of "Taylorized" Systems

Several of the consultants who installed Taylor's system in Philadelphia became important in their own right and were responsible for the spread of "Taylorized" management systems far beyond the relative handful of companies that the founder implemented himself. His assistants worked on the two installations that became Taylor's showpieces of scientific management for visitors to Philadelphia, Link-Belt and the Tabor Manufacturing Company, and implemented some elements of the system at Philadelphia's Frankford Arsenal and the Navy Yard. The Link-Belt Company also led to the longest lasting direct Philadelphia descendant of Taylor's original group, the Day & Zimmermann management consulting firm. Although later diversified, it was started as Dodge & Day by Link-Belt founder's son Kern Dodge (1880-1958) and his friend Charles Day (1879-1931). After helping "modernize" Link-Belt with Taylor's consultants, they formed their own company and began doing the same for other clients, often in consultation with Taylor, starting with the Jeanesville Iron Works in Hazleton, Pennsylvania.

Another close confidante of Taylor's, Morris L. Cooke (1872-1960), broadened the reach of the system to Philadelphia's city government and marked the further integration of scientific management with the Progressive movement, when he became the city's director of public works in 1911 and introduced several efficiency measures. Cooke wrote: "That these principles-enunciated by Taylor-can be applied to city work as they have been applied to scores of different kinds of industrial work is to me only too obvious. It opens up a field of endeavor which staggers the imagination." He followed up by firing a thousand city employees for inefficiency, brought in two hundred "expert" engineers to direct highway workers, and claimed to have saved the city some five million dollars. His attempt to convince President Woodrow Wilson to turn Washington, D.C., into a municipal laboratory, however, failed.

The "efficiency craze" spread across the country and the world after future Supreme Court justice Louis Brandeis coined the term "Scientific Management" during the famous Eastern Rate Case in 1910 and Taylor published his Principles of Scientific Management the next year. But paradoxically, the founder's original strict interpretation of the system was diluted as more "efficiency experts" rushed to take advantage of the new opportunities. In 1911 Taylor complained that Harrington Emerson (1853-1931), a former close adherent of the Taylor method, had told Navy Yard officers that he could install all the "important" parts of Taylor's system in a few short months. Emerson later introduced his quicker and cheaper alternative in many other plants, including Lukens Steel in Coatesville, Pennsylvania.

Other companies like DuPont decided to try converting to "scientific" management methods on their own. Unfortunately, DuPont began its experiment in its Repauno High Explosives Operating Department near Gibbstown, New Jersey, in 1913. Although some employees complained that foremen were "rushing the men," the project continued until a massive explosion killed four workers. The experiment was moved to another building. It, too, suffered an explosion soon after, killing several more men. Interest in putting an efficiency scheme into practice did not resume until the Great Depression induced the company to find new ways to reduce costs.

Charles Bedaux, Simplifier

When DuPont did again embark on systematizing its operations, it did so with the consulting company of the colorful and controversial Charles Bedaux (1886-1944). His simple and relatively inexpensive program promised a quick return on investment without the lengthy and painstaking selection of workers, plant redesign, and job study required in Taylor's approach. In addition to DuPont, Lukens Steel also switched to the Bedaux plan, as did numerous other Delaware Valley companies. At Campbell Soup' s flagship plant in Camden the system became the flashpoint for innumerable conflicts between workers and management for several decades starting in the early 1930s. Soup plant workers complained that the "B" system was difficult to understand, targets were hard to meet (resulting in hundreds of firings), and that management changed targets unfairly. Yet the efficiency program was a central element of Campbell's successful drive to keep costs down and profits high. Workers at Keasbey and Mattison, an asbestos shingle manufacturer and the largest employer in Ambler, Pennsylvania, however, were more successful in ending the Bedaux system there; the company threw the system out in 1937 due to "labor unrest."

By World War II, time-and-motion study and job standards were no longer a novelty. Young women working in the secretarial pool at the Army Ordnance offices on South Broad Street and machine tenders in steel fabrication plants had become accustomed to "efficiency experts" timing and monitoring their work. Later management trends claimed to replace Taylorism with newer approaches to work and workers, but most of them were deeply indebted to the Germantown native. The central concepts of "Lean Production," for example, were the elimination of waste-especially waste of time-and continuous improvement, all with the goal of increasing productivity. Both original scientific management and its later incarnations also claimed to be in the best interest of workers.

The central argument for the beneficial effects of Taylorism for employees rested on the premise that the proceeds from increased productivity would be shared equitably between management and labor, by the mechanism of the system's bonus incentive plan. It has even been credited with raising the standard of living for Philadelphia's working class generally. The first objection to this argument concerned all those left out of it. Taylor himself said there were very few "first-class men" for any job, and those who could not make the grade, whether at Bethlehem Steel or Campbell Soup, were dismissed. Those who survived the cut worked much harder than before and lost any discretion they previously had in determining how they performed their jobs, but they did see increased wages-in companies that strictly followed Taylor's rules. The cardinal principle here was that management would not raise the amount of work needed to reach the bonus level once a job had been "scientifically" studied and rated. Very few companies kept to this precept for very long, however.

At its core, Taylorism was a class philosophy, in which strict but benevolent masters would provide well for their subordinates as long as they did exactly as they were told. Far more responsible for raising Philadelphia's workers' standard of living were the efforts they expended themselves. In the defensive strikes of unionized craftsmen early in the twentieth century and the mass unionization drives by industrial workers during the Great Depression and World War II, workers fought for and often won a greater share of the increased productivity resulting from Taylorism and other efficiency schemes.

Daniel Sidorick teaches labor history at Rutgers University New Brunswick. He is the author of Condensed Capitalism: Campbell Soup and the Pursuit of Cheap Production in the Twentieth Century.

Copyright 2015, Rutgers University

Braverman, Harry. Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century. New York, Monthly Review Press, 1974.

Kanigel, Robert. The One Best Way: Frederick Winslow Taylor and the Enigma of Efficiency. New York: Viking, 1997.

Nelson, Daniel. Frederick W. Taylor and the Rise of Scientific Management. Madison: University of Wisconsin Press, 1980.

Nelson, Daniel, ed. A Mental Revolution: Scientific Management since Taylor. Columbus: Ohio State University Press, 1992.

Sidorick, Daniel. Condensed Capitalism: Campbell Soup and the Pursuit of Cheap Production in the Twentieth Century. Ithaca: Cornell University Press, 2009.

Taylor, Frederick Winslow. The Principles of Scientific Management. New York: Harper & Brothers, 1911.

Wrege, Charles D. and Ronald G. Greenwood. Frederick W. Taylor, the Father of Scientific Management: Myth and Reality. Homewood, Ill.: Business One Irwin, 1991.

Frederick Winslow Taylor Collection, Samuel C. Williams Library, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, N.J.

Henry Noll ("Schmidt") Historical Marker. Marker Location: E. Third St. east of Fillmore Street, Bethlehem, Pa.

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The Scientific Management movement was born in early twentieth-century Philadelphia factories but spread rapidly, transforming not only management techniques but also popular conceptions of industrialized society itself. According to its founders, the system simply sought the one best way to perform any task.

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Constructivism and Structured Academic Controversy Constructivism is a philosophical view that describes how students and their teacher interact; how classroom time and space are used, and how control within the ...

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November 1999 | Volume 57 | Number 3
The Constructivist Classroom Pages 18-24

Martin G. Brooks and Jacqueline Grennon Brooks

One such foundational notion is that students will learn on demand. This bedrock belief is manifested in the traditional scope and sequence of a typical course of study and, more recently, in the new educational standards and assessments. This approach to schooling is grounded in the conviction that all students can and will learn the same material at the same time. For some students, this approach does indeed lead to the construction of knowledge. For others, however, it does not.

The people working directly with students are the ones who must adapt and adjust lessons on the basis of evolving needs. Constructivist educational practice cannot be realized without the classroom teacher's autonomous, ongoing, professional judgment. State education departments could and should support good educational practice. But too often they do not.

Their major flaw is their focus on high-stakes accountability systems and the ramifications of that focus on teachers and students. Rather than set standards for professional practice and the development of local capacity to enhance student learning, many state education departments have placed even greater weight on the same managerial equation that has failed repeatedly in the past: State Standards = State Tests; State Test Results = Student Achievement; Student Achievement = Rewards and Punishments.

We are not suggesting that educators should not be held accountable for their students' learning. We believe that they should. Unfortunately, we are not holding our profession accountable for learning, only for achievement on high-stakes tests. As we have learned from years of National Assessment of Educational Progress research, equating lasting student learning with test results is folly.

The Emerging Research from Standards-Driven States

In recent years, many states have initiated comprehensive educational reform efforts. The systemic thinking that frames most standards-based reform efforts is delectably logical: Develop high standards for all students; align curriculum and instruction to these standards; construct assessments to measure whether all students are meeting the standards; equate test results with student learning; and reward schools whose students score well on the assessments and sanction schools whose students don't.

Predictably, this simple and linear approach to educational reform is sinking under the weight of its own flaws. It is too similar to earlier reform approaches, and it misses the point. Educational improvement is not accomplished through administrative or legislative mandate. It is accomplished through attention to the complicated, idiosyncratic, often paradoxical, and difficult to measure nature of learning.

A useful body of research is emerging from the states. With minor variations, the research indicates the following:

Test scores are generally low on the first assessment relating to new standards. Virginia is an extreme example of this phenomenon: More than 95 percent of schools failed the state's first test. In New York, more than 50 percent of the state's 4th graders were deemed at risk of not graduating in 2007 after taking that state's new English language arts test in 1999.

Failure, or the fear of failure, breeds success on subsequent tests. After the first administration of most state assessments, schools' scores rise because educators align curriculum closely with the assessments, and they focus classroom instruction directly on test-taking strategies.

To increase the percentages of students passing the state assessments-and to keep schools off the states' lists of failing schools-local district spending on student remediation, student test-taking skills, and faculty preparation for the new assessments increases.

Despite rising test scores in sub-sequent years, there is little or no evidence of increased student learning. A recent study by Kentucky's Office of Educational Accountability (Hambleton et al., 1995) suggests that test-score gains in that state are a function of students' increasing skills as test takers rather than evidence of increased learning.

When Tests Constrict Learning

Learning is a complex process through which learners constantly change their internally constructed understandings of how their worlds function. New information either transforms their current beliefs-or doesn't. The efficacy of the learning environment is a function of many complex factors, including curriculum, instructional methodology, student motivation, and student developmental readiness. Trying to capture this complexity on paper-and-pencil assessments severely limits knowledge and expression.

Inevitably, schools reduce the curriculum to only that which is covered on tests, and this constriction limits student learning. So, too, does the undeviating, one-size-fits-all approach to teaching and assessment in many states that have crowned accountability king. Requiring all students to take the same courses and pass the same tests may hold political capital for legislators and state-level educational policymakers, but it contravenes what years of painstaking research tells us about student learning. In discussing the inordinate amount of time and energy devoted to preparing students to take and pass high-stakes tests, Angaran (1999) writes

Ironically, all this activity prepares them for hours of passivity. This extended amount of seat time flies in the face of what we know about how children learn. Unfortunately, it does not seem to matter. It is, after all, the Information Age. The quest for more information drives us forward. (P. 72)

We are not saying that student success on state assessments and classroom practices designed to foster understanding are inherently contradictory. Teaching in ways that nurture students' quests to resolve cognitive conflict and conquer academic challenges fosters the creative problem solving that most states seek. However, classroom practices designed to prepare students for tests clearly do not foster deep learning that students apply to new situations. Instead, these practices train students to mimic learning on tests.

Many school districts question the philosophical underpinnings of the dominant test-teach-test model of education and are searching for broader ways for students to demonstrate their knowledge. However, the accountability component of the standards movement has caused many districts to abandon performance-based assessment practices and refocus instead on preparing students for paper-and-pencil tests. The consequences for districts and their students are too great if they don't.

Constructivism in the Classroom

Learners control their learning. This simple truth lies at the heart of the constructivist approach to education.

As educators, we develop classroom practices and negotiate the curriculum to enhance the likelihood of student learning. But controlling what students learn is virtually impossible. The search for meaning takes a different route for each student. Even when educators structure classroom lessons and curriculums to ensure that all students learn the same concepts at the same time, each student still constructs his or her own unique meaning through his or her own cognitive processes. In other words, as educators we have great control over what we teach, but far less control over what students learn.

Shifting our priorities from ensuring that all students learn the same concepts to ensuring that we carefully analyze students' understandings to customize our teaching approaches is an essential step in educational reform that results in increased learning. Again, we must set standards for our own professional practice and free students from the anti-intellectual training that occurs under the banner of test preparation.

The search for understanding motivates students to learn. When students want to know more about an idea, a topic, or an entire discipline, they put more cognitive energy into classroom investigations and discussions and study more on their own. We have identified five central tenets of constructivism (Grennon Brooks & Brooks, 1993).

First, constructivist teachers seek and value students' points of view. Knowing what students think about concepts helps teachers formulate classroom lessons and differentiate instruction on the basis of students' needs and interests.

Second, constructivist teachers structure lessons to challenge students' suppositions. All students, whether they are 6 or 16 or 60, come to the classroom with life experiences that shape their views about how their worlds work. When educators permit students to construct knowledge that challenges their current suppositions, learning occurs. Only through asking students what they think they know and why they think they know it are we and they able to confront their suppositions.

Third, constructivist teachers recognize that students must attach relevance to the curriculum. As students see relevance in their daily activities, their interest in learning grows.

Fourth, constructivist teachers structure lessons around big ideas, not small bits of information. Exposing students to wholes first helps them determine the relevant parts as they refine their understandings of the wholes.

Finally, constructivist teachers assess student learning in the context of daily classroom investigations, not as separate events. Students demonstrate their knowledge every day in a variety of ways. Defining understanding as only that which is capable of being measured by paper-and-pencil assessments administered under strict security perpetuates false and counterproductive myths about academia, intelligence, creativity, accountability, and knowledge.

Opportunities for Constructing Meaning

Recently, we visited a classroom in which a teacher asked 7th graders to reflect on a poem. The teacher began the lesson by asking the students to interpret the first two lines. One student volunteered that the lines evoked an image of a dream. "No," he was told, "that's not what the author meant." Another student said that the poem reminded her of a voyage at sea. The teacher reminded the student that she was supposed to be thinking about the first two lines of the poem, not the whole poem, and then told her that the poem was not about the sea. Looking out at the class, the teacher asked, "Anyone else?" No other student raised a hand.

In another classroom, a teacher asked 9th graders to ponder the effect of temperature on muscle movement. Students had ice, buckets of water, gauges for measuring finger-grip strength, and other items to help them consider the relationship. The teacher asked a few framing questions, stated rules for handling materials safely, and then gave the students time to design their experiments. He posed different questions to different groups of students, depending on their activities and the conclusions that they seemed to be drawing. He continually asked students to elaborate or posed contradictions to their responses, even when they were correct.

As the end of the period neared, the students shared initial findings about their investigations and offered working hypotheses about the relationship between muscle movement and temperature. Several students asked to return later that day to continue working on their experiments.

Let's consider these two lessons. In one case, the lesson was not conducive to students' constructing deeper meaning. In the other case, it was. The 7th grade teacher communicated to her students that there is one interpretation of the poem's meaning, that she knew it, and that only that interpretation was an acceptable response. The students' primary quest, then, was to figure out what the teacher thought of the poem.

The teacher spoke to her students in respectful tones, acknowledging each one by name and encouraging their responses. However, she politely and calmly rejected their ideas when they failed to conform to her views. She rejected one student's response as a misinterpretation. She dismissed another student's response because of a procedural error: The response focused on the whole poem, not on just the designated two lines.

After the teacher told these two students that they were wrong, none of the other students volunteered interpretations, even though the teacher encouraged more responses. The teacher then proceeded with the lesson by telling the students what the poet really meant. Because only two students offered comments during the lesson, the teacher told us that a separate test would inform her whether the other students understood the poem.

In the second lesson, the teacher withheld his thoughts intentionally to challenge students to develop their own hypotheses. Even when students' initial responses were correct, the teacher challenged their thinking, causing many students to question the correctness of their initial responses and to investigate the issue more deeply.

Very few students had awakened that morning thinking about the relationship between muscle movement and temperature. But, as the teacher helped students focus their emerging, somewhat disjointed musings into a structured investigation, their engagement grew. The teacher provoked the students to search for relevance in a relationship they hadn't yet considered by framing the investigation around one big concept, providing appropriate materials and general questions, and helping the students think through their own questions. Moreover, the teacher sought and valued his students' points of view and used their comments to assess their learning. No separate testing event was required.

What Constructivism Is and Isn't

As constructivism has gained support as an educational approach, two main criticisms have emerged. One critique of constructivism is that it is overly permissive. This critique suggests that constructivist teachers often abandon their curriculums to pursue the whims of their students. If, for example, most of the students in the aforementioned 9th grade science class wished to discuss the relationship between physical exercise and muscle movement rather than pursue the planned lesson, so be it. In math and science, critics are particularly concerned that teachers jettison basic information to permit students to think in overly broad mathematical and scientific terms.

The other critique of constructivist approaches to education is that they lack rigor. The concern here is that teachers cast aside the information, facts, and basic skills embedded in the curriculum-and necessary to pass high-stakes tests-in the pursuit of more capricious ideas. Critics would be concerned that in the 7th grade English lesson described previously, the importance of having students understand the one true main idea of the poem would fall prey to a discussion of their individual interpretations.

Both of these critiques are silly caricatures of what an evolving body of research tells us about learning. Battista (1999), speaking specifically of mathematics education, writes,

Many . . . conceive of constructivism as a pedagogical stance that entails a type of non-rigorous, intellectual anarchy that lets students pursue whatever interests them and invent and use any mathematical methods they wish, whether those methods are correct or not. Others take constructivism to be synonymous with "discovery learning" from the era of "new math," and still others see it as a way of teaching that focuses on using manipulatives or cooperative learning. None of these conceptions is correct. (P. 429)

Organizing a constructivist classroom is difficult work for the teacher and requires the rigorous intellectual commitment and perseverance of students. Constructivist teachers recognize that students bring their prior experiences with them to each school activity and that it is crucial to connect lessons to their students' experiential repertoires. Initial relevance and interest are largely a function of the learner's experiences, not of the teacher's planning. Therefore, it is educationally counterproductive to ignore students' suppositions and points of view. The 7th grade English lesson is largely nonintellectual. The 9th grade science lesson, modeled on how scientists make state-of-the-art science advancements, is much more intellectually rigorous.

Moreover, constructivist teachers keep relevant facts, information, and skills at the forefront of their lesson planning. They usually do this within the context of discussions about bigger ideas. For example, the dates, battles, and names associated with the U.S. Civil War have much more meaning for students when introduced within larger investigations of slavery, territorial expansion, and economics than when presented for memorization without a larger context.

State and local curriculums address what students learn. Constructivism, as an approach to education, addresses how students learn. The constructivist teacher, in mediating students' learning, blends the what with the how. As a 3rd grader in another classroom we visited wrote to his teacher, "You are like the North Star for the class. You don't tell us where to go, but you help us find our way." Constructivist classrooms demand far more from teachers and students than lockstep obeisance to prepackaged lessons.

The Effects of High-Stakes Accountability

As we stated earlier, the standards movement has a grand flaw at the nexus of standards, accountability, and instructional practice. Instructional practices designed to help students construct meaning are being crowded out of the curriculum by practices designed to prepare students to score well on state assessments. The push for accountability is eclipsing the intent of standards and sound educational practice.

Let's look at the effects of high-stakes accountability systems. Originally, many states identified higher-order thinking as a goal of reform and promoted constructivist teaching practices to achieve this goal. In most states, however, policymakers dropped this goal or subsumed it into other goals because it was deemed too difficult to assess and quantify. Rich evidence relating to higher-order thinking is available daily in classrooms, but this evidence is not necessarily translatable to paper-and-pencil assessments. High-stakes accountability systems, therefore, tend to warp the original visions of reform.

Education is a holistic endeavor. Students' learning encompasses emerging understandings about themselves, their relationships, and their relative places in the world. In addition to academic achievement, students develop these understandings through nonacademic aspects of schooling, such as clubs, sports, community service, music, arts, and theater. However, only that which is academic and easily measurable gets assessed, and only that which is assessed is subject to rewards and punishments. Jones and Whitford (1997) point out that Kentucky's original educational renewal initiative included student self-sufficiency and responsible group membership as goals, but these goals were dropped because they were deemed too difficult to assess and not sufficiently academic.

Schools operating in high-stakes accountability systems typically move attention away from principles of learning, student-centered curriculum, and constructivist teaching practices. They focus instead on obtaining higher test scores, despite research showing that higher test scores are not necessarily indicative of increased student learning.

Historically, many educators have considered multiple-choice tests to be the most valid and reliable form of assessment-and also the narrowest form of assessment. Therefore, despite the initial commitment of many states to performance assessment, which was to have been the cornerstone of state assessment efforts aligned with broader curriculum and constructivist instructional practices, multiple-choice questions have instead remained the coin of the realm. As Jones and Whitford (1997) write about Kentucky,

The logic is clear. The more open and performance based an assessment is, the more variety in the responses; the more variety in the responses, the more judgment is needed in scoring; the more judgment in scoring, the lower the reliability. . . . At this point, multiple-choice items have been reintroduced, performance events discontinued. (P. 278)

Ironically, as state departments of education and local newspapers hold schools increasingly accountable for their test results, local school officials press state education departments for greater guidance about material to be included on the states' tests. This phenomenon emboldens state education departments to take an even greater role in curriculum development, as well as in other decisions typically handled at the local level, such as granting high school diplomas, determining professional development requirements for teachers, making special education placements, and intervening academically for at-risk students. According to Jones and Whitford (1997),

[In Kentucky] there has been a rebound effect. Pressure generated by the state test for high stakes accountability has led school-based educators to pressure the state to be more explicit about content that will be tested. This in turn constrains local school decision making about curriculum. This dialectical process works to increase the state control of local curriculum. (P. 278)

Toward Educational Reform

Serious educational reform targets cognitive changes in students' thinking. Perceived educational reform targets numerical changes in students' test scores. Our obsession with the perception of reform, what Ohanian (1999) calls "the mirage theory of education," is undermining the possibility of serious reform.

History tells us that it is likely that students' scores on state assessments will rise steadily over the next decade and that meaningful indexes of student learning generally will remain flat. It is also likely that teachers, especially those teaching in the grades in which high-stakes assessments are administered, will continue to narrow their curriculum to match what is covered on the assessments and to use instructional practices designed to place testing information directly in their students' heads.

We counsel advocacy for children. And vision. And courage.

Focus on student learning. When we design instructional practices to help students construct knowledge, students learn. This is our calling as educators.

Keep the curriculum conceptual. Narrowing curriculum to match what is covered on state assessments results in an overemphasis on the rote memorization of discrete bits of information and pushes aside big ideas and intellectual curiosity. Keep essential principles and recurring concepts at the center.

Assess student learning within the context of daily instruction. Use students' daily work, points of view, suppositions, projects, and demonstrations to assess what they know and don't know, and use these assessments to guide teaching.

Initiate discussions among administrators, teachers, parents, school boards, and students about the relationship among the state's standards, the state's assessments, and your district's mission. Ask questions about what the assessments actually assess, the instructional practices advocated by your district, and the ways to teach a conceptual curriculum while preparing students for the assessments. These are discussions worth having.

Understand the purposes of accountability. Who wants it, and why? Who is being held accountable, and for what? How are data being used or misused? What are the consequences of accountability for all students, especially for specific groups, such as special education students and English language learners?

Students must be permitted the freedom to think, to question, to reflect, and to interact with ideas, objects, and others-in other words, to construct meaning. In school, being wrong has always carried negative consequences for students. Sadly, in this climate of increasing accountability, being wrong carries even more severe consequences. But being wrong is often the first step on the path to greater understanding.

We observed a 5th grade teacher return a test from the previous day. Question 3 was, "There are 7 blue chips and 3 green chips in a bag. If you place your hand in the bag and pull out 1 chip, what is the probability that you will get a green chip?" One student wrote,"You probably won't get one." She was "right"-and also "wrong." She received no credit for the question.

References

Angaran, J. (1999, March). Reflection in an age of assessment. Educational Leadership, 56, 71-72.

Grennon Brooks, J., & Brooks, M. G. (1993). In search of understanding: The case for constructivist classrooms. Alexandria, VA: ASCD.

Hambleton, R., Jaeger, R. M., Koretz, D., Linn, R. L., Millman, J., & Phillips, S. E. (1995). Review of the measurement quality of the Kentucky instructional results information system 1991-1994. (Report prepared for the Kentucky General Assembly.) Frankfort, KY: Office of Educational Accountability.

Jones, K., & Whitford, B. L. (1997, December). Kentucky's conflicting reform principles: High stakes accountability and student performance assessment. Phi Delta Kappan, 78(4), 276-281.

Ohanian, S. (1999). One size fits few. Portsmouth, NH: Heinemann.

Martin G. Brooks (email: vsdist1@li.net) is Superintendent, Valley Stream Central High School District, One Ken Rd., Valley Stream, NY 11582. Jacqueline Grennon Brooks (e-mail: jgbrooks@notes.cc.sunysb.edu) is Associate Professor, Professional Education Program, State University of New York at Stony Brook, Stony Brook, NY 11794-3733.

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November 1999 | Volume 57 | Number 3 The Constructivist Classroom Pages 18-24 Martin G. Brooks and Jacqueline Grennon Brooks One such foundational notion is that students will learn on demand. This bedrock belief is manifested in the traditional scope and sequence of a typical course of study and, more recently, in the new educational standards and assessments.

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Published: Mon, 5 Dec 2016

The previous two chapters presented the literature review pertinent to this study. This chapter describes the methodology that guided this study. Methodology refers to a basic set of beliefs that guide the research methods of data collection and analysis (Guba, 1990; Denzin & Lincoln, 2005). It is imperative that the ontological and epistemological stance of a study have the capacity to facilitate the achievement of a study's objectives. This chapter establishes the context of the study from a philosophical and methodological perspective. The chapter consist of two sections. First section justifies use of a qualitative approach followed by discussion of various research paradigms used in health and social care research. The next section explores ontological, epistemological, methodological and ethical concepts related to the chosen research paradigm in more detail.

Selection of a particular perspective is heavily influenced and shaped by who the researcher is and what their beliefs are about the world and how it can be explored. It is also influenced by the specific purpose of the research. The purpose of this research was to generate a theory to explain the meaning of IPV from the perspective of Pakistani men and women. The objective warranted use of a qualitative approach. Selection of this methodological approach was influenced by various factors. Firstly, I believe that the issue of IPV occurs in the context of a particular society and culture and in order to understand the definitions of IPV from the perspective of a particular population, it is important to consider cultural and social influences. Secondly, I believe that individuals vary and that each individual perceives, experiences, represents and recreates reality differently. Thirdly, in-depth exploration of individuals' perceptions and perspectives requires a considerable amount of researcher's involvement. The researcher themselves brings their own perceptions, values, beliefs, and experiences related to the area of investigation to the research and thus has an influence on the conduct and findings of a research study. A qualitative approach was congruent with these requirements, as a qualitative approach emphasises process and meanings, the socially constructed nature of reality, and an intimate relationship between the researcher and the area under study (Denzin & Lincoln, 1998). There are various methodological stances that can be adopted within a qualitative approach. Therefore, the next step was selection of a research paradigm which could guide this study.

4.1 Research Paradigm

Research paradigm refers to a set of beliefs and feelings about the world and how it should be explored and studied (Denzin & Lincoln, 2003). It "â€¦is a philosophical model or framework originating in a worldview and belief system based on a particular ontology and epistemology and shared by a scientific community" (Holloway, 1997, p. 114). The research paradigm acts as a lens that the researcher uses to view the world; therefore, it reflects the worldview of the researcher. Various research paradigms that direct public health and social research include positivism, post positivism, critical theory and interpretivism or constructivism (Guba & Lincoln, 1998). A brief explanation of each paradigm and justification of its selection or rejection for this study is provided in the following section.

4.1. i Positivism and Post positivism

Positivism argues for the existence of a true and objective reality that can be studied through applying the methods and principles of natural sciences and scientific inquiry. It maintains that "the object of study is independent of researchers; knowledge is discovered and verified through direct observations or measurements of phenomena; facts are established by taking apart a phenomenon to examine its component parts" (Krauss, 2005, p. 759). According to this paradigm, the role of the researcher is to provide material for the development of laws by testing theories (Bryman, 2008). Positivists believe in five principles which include phenomenalism (knowledge confirmed by the senses can be regarded as knowledge), deductivism (the purpose of theory is to generate hypotheses that can be tested to make laws), inductivism (the gathering of facts provides the basis for laws and knowledge), objectivism (science should be value-free) and scientific statements (Bryman, 2008).

Post positivism is considered a contemporary paradigm that developed as a result of the criticism of positivism. Like positivists, post positivists also believe in the existence of a single reality, however, they acknowledge that reality can never be fully known and efforts to understand reality are limited owing to the human beings' sensory and intellectual limitations (Guba, 1990). The aim of post positivist research is also prediction and explanation. Like positivists, post positivists also strive to be objective, neutral and ensure that the findings fit with the existing knowledge base. However, unlike positivists, they acknowledge and spell out any predispositions that may affect the objectivity (Doucet et al., 2010).

Positivism and post positivism were precluded from use in this study for several reasons. Firstly, research conducted under both of these paradigms is usually quantitative where a hypothesis is tested while the researcher remains objective and separate from the area of investigation. However, as a researcher, I was embedded within the research area as I belong to the same population and thus may hold the same values and beliefs as research participants. I belief that this could be a source of bias within a post positivist paradigm given that I could not be objective and detached from the substantive topic of the study and participants. Secondly, the focus of the research was to better understand the phenomenon of IPV in the Pakistani population. The purpose of the study was not to test a theory, but to ascertain if a more complete picture of the phenomenon of IPV from the perspectives of participants could be developed. This required exploring the perceptions and perspective of different people, all of whom may have a different version and perception of reality. Thirdly, both of these paradigms assume that experiences and perceptions can be reduced to objective measurements and that standardised questionnaires (such as the conflict tactic scale) should be used. However, if one believes that definitions and interpretations develop from experiences, observations, perceptions, and that experience and perceptions are subjective in nature, using standardised questionnaires and objective outcome measurements as a proxy of experiences and perceptions can only provide limited information. It cannot capture participants' conceptualisation of IPV or improve understanding of what IPV means to them. Finally, both of these paradigms believe in the existence of a reality independent of social, cultural, political, economical factors, and therefore assume that the questionnaire developed in one culture can be applied in another culture or setting without alterations. However, I believe that people's perceptions and perspectives about a phenomenon are shaped and influenced by the familial, emotional, psychological, social, cultural, political, and economical dimensions of their surroundings and it is important to take in to account the above mentioned factors and the context in which a certain phenomenon occurs. Owing to these reasons, positivism and post positivism were considered unsuitable for the present study.

4.1.ii Critical Theory:

The third research paradigm of critical theory evolved in Germany in the early 1920s (Carroll, 2004). It is also known as the transformative (Mertens, 2005) and critical-ideological paradigm (Ponterotto, 2005). Critical theory uses historical realism to define reality and maintains that realities are shaped by social, political, economic, cultural, ethnic and gender factors, and that these factors are responsible for oppression (Guba & Lincoln, 1994). Research based on this paradigm not only aims to understand society but to critique, change and create a new reality (Guba & Lincoln, 1994). Critical researchers believe that participants are experts in their knowledge and that the role of the researcher is to facilitate and stimulate change. It maintains that a true reality exists (Guba, 1990), researcher and participants both influence inquiry (Guba & Lincoln, 1994) and that the interaction with the researcher facilitates empowerment and liberation from oppression of the participants (Ponterotto, 2005). Some researchers also argue that reality is constructed though the interactive nature of the relationship between researcher and participants (Ford-Gilboe et al., 1995).

The critical theory paradigm was also not considered appropriate for this study. Firstly, the aim of the research conducted under a critical theory paradigm would be to bring about change. Secondly, the critical theory paradigm assumes that the knowledge about what needs to change exists and that the aim of a study should be to facilitate empowerment and emancipation of the participants. The purpose of the present study was not to bring about change but to better understand the phenomenon of IPV. It aimed to understand the meaning and definitions of IPV. Therefore, I did not consider critical theory to be an appropriate paradigm for this research.

4.1.iii Interpretivism/ Constructivism:

The fourth paradigm I considered was constructivism. It is also known as the interpretive, humanistic, and naturalistic paradigm. The origin of constructivism can be traced back to Berger and Luckmann's (1967) The Social Construction of Reality and Lincoln and Guba's (1985) Naturalistic Inquiry (Doucet et al., 2010). This paradigm maintains that social subjects and problems cannot be studied through positivism. Constructivists believe that the world is multifaceted and that there are multiple realities which are constructed, experienced and interpreted differently by different people. People give meaning to their experiences based on their experience of interaction with others, and the community and social system in which they live. Constructivism places "â€¦ emphasis and value of human, interpretative aspects of knowing about the social world, and the significance of the investigator's own interpretations and understanding of the phenomenon being studied" (Snap & Spencer, 2003, p. 7). Constructivists assume that reality is not a fixed entity, rather individuals construct their own reality that may change as the individual becomes more informed. The paradigm maintains that knowledge is contrasted, and is based not only on observable facts, but also on individual values, beliefs, and understanding. Constructivist research aims to present multiple, holistic, competing, and often conflicting realities of involved parties including researchers and participants (Guba & Lincoln, 1994). The researcher's role and effect is acknowledged and together the researcher and the participants reach new constructions which are more informed, sophisticated and real to those individuals who created it. The constructed knowledge can then be transferred to other settings and contexts to enable others to examine if the constructions fit with their experiences in their own environment and contexts (Guba & Lincoln, 1998).

This paradigm was considered to be most appropriate for the present research, as it has the capacity to capture people's individual subjective perceptions and experiences of IPV. It also acknowledges the role of the researcher who brings their own experiences and perceptions related to the area under investigation. Finally it accepts that perceptions and experiences of reality are influenced by the surrounding context, culture and socio-political environment in which people live.

4.2 Conceptual Components of the Research Paradigm

The underpinning assumptions that define a research paradigm can be ascertained through the ontological (form and nature of reality), epistemological (the basic belief about knowledge, what can be known), methodological (the method used to know the unknown) and ethical questions (how to be a moral person within the world and research paradigm) (Guba & Lincoln, 1994; Denzin & Lincoln, 2003). The following section provides a more detailed account of these four conceptual components in relation to this study.

4.2.i Ontology

The term ontology refers to the underlying belief of the researcher about the nature of reality and what can be known. It is important to have a congruency and fit between the ontology and the research purpose. The purpose of this study was to develop a theory to define and explain IPV from the perspective of Pakistani men and women. The aim of the study implicitly maintains that exploring individual experiences and perceptions can help understand the meaning and concepts related to a particular social issue such as IPV. According to Snape and Spencer (2003) social phenomena are believed to exist independently of people's representations of them but are only accessible through those representations" (p. 13). This refers to the critical realist viewpoint, which lies between realism and idealism.

Realism maintains that a reality exists independently regardless of people's awareness or interest in it (Smith, 1983). For realists, the purpose of research is to explore and examine theories in an attempt to establish the truth. Idealism, on the other hand, discards the notion of independent reality and maintains that "there exist multiple, socially constructed realities ungoverned by laws, natural or otherwise â€¦ these constructions are devised by individuals as they attempt to make sense of their experiences" (Guba & Lincoln, 1989, p. 86). For idealists, the aim of research is to uncover various perspectives about a phenomenon of interest, thus to reveal realities and not truths (Charmaz, 2000). For idealists, multiple realities, that are context bound, exist side-by-side. However, the question arises that if there are multiple realities and if the purpose of qualitative research is to reveal another reality then what is the practical use of it? Findings identified by the researcher just become another reality among realities that already exist (Murphy et al., 1998). In order to resolve this dilemma, a third position of "critical realism" or "subtle realism" is suggested. This position maintains that individual experiences, interpretations and societal and cultural contexts influence the ways a reality is experienced, perceived, represented and described. Critical realism maintains that there are multiple realities, which are represented in multiple ways and that such representations are socially constructed and mediated (constructivism). This study is based on the ontological stance of critical realism.

The perspectives of Pakistani men and women about IPV are explored and it is acknowledged that socio-cultural factors of Pakistani society have an impact on these perspectives. There may be individual differences between people's perceptions, but at the same time, there could be a shared or collective representation of IPV as defined by the study participants. Critical realist ontology supports this notion and, therefore, is adopted for this study.

4.2.ii Epistemology

The term epistemology comes from the Greek word "epistêmê" which refers to knowledge. It can be defined as a philosophy of knowledge and is concerned with various questions such as: "What is the relationship between the knower and what is known? How do we know what we know? What counts as knowledge?" (Krauss, 2005, p. 759). The epistemology of a study develops the theoretical framework of a study and clarifies how a researcher knows about the world generally and about the research subject particularly. The theoretical perspective of symbolic interactionism forms the underpinning epistemological basis of this research.

Symbolic interactionism is a sociological perspective which emphasises the importance of micro-scale social interactions. It is derived from pragmatism and especially the work of the social psychologist George Herbert Mead (Strauss & Corbin, 1990). Mead believed that social interaction and the social context in which a person lives has an influence on a person's sense of self and that the individual mind can exist only in relation to other minds who hold similar meaning. Symbolic interactionism postulates that people build their realities through social interactions in which shared symbols such as words, clothing, and gestures are used to communicate meaning (Fassinger, 2005). Herbert Blumer, a student and an interpreter of Mead, took his thoughts further. He came up with the term symbolic interactionism and developed a comprehensive and influential summary of this perspective. Blumer (1969) set up three important premises of the perspective that were:

Human beings act toward things according to the meanings they ascribe to them.

The meanings of such things are derived from social interactions.

Meanings constantly modify through an interpretative process within the person in dealing with the things they encounter.

Based on these premises, research studies are conducted to explore social issues and people in the social context they live in. Constructivism, itself, is a type of symbolic interactionism. Symbolic interactionism is one of the earliest theories that influenced qualitative research. Early research based on this perspective is criticised for being too descriptive and lacking in interpretation and explanation of the actions (Gerhardt, 1990). However, the development of grounded theory attempted to address this criticism to a certain extent by providing a qualitative, yet, systematic, inductive, iterative and rigorous approach to interpret data to develop a theory (Glaser & Strauss, 1967; Charmaz, 2000). Symbolic interactionism and grounded theory are strongly compatible. "Both the theoretical perspective and the method assume an agentic actor, the significance of studying processes, the emphasis on building useful theory from empirical observations, and the development of conditional theories, that address specific realities" (Bryant & Charmaz, 2007, p. 21). Grounded theorists examine the meanings created in social relationships and try to discern how groups of people define their realities on the basis of their experiences and understandings of interpersonal interactions (Fassinger, 2005). Symbolic interactionism seemed to be an appropriate theoretical perspective for this research study. Firstly, the study aimed to explain the meaning and perspective of Pakistani men and women about IPV. It aimed to focus on how people define IPV in marital relationships. Secondly, the study acknowledges the influence of society and culture on people's perception about phenomenon of interest. Thirdly, experiencing IPV can have an effect on how the person views him/herself and the world surrounding them. Based on these grounds, the symbolic interactionism was identified as an appropriate theoretical perspective to guide this study.

4.2.iii Methodology

Methodology refers to theories of social reality and the procedures, methods, and techniques to aggregate and analyze data. It acts as a bridge between the ontological and epistemological grounds of a study and the methods used to conduct the research (described in next chapter). For this study, a qualitative methodology was used to address the research question. It facilitates understanding of a social problem and to develop a complex but holistic picture of the problem under investigation with subjective experiences, feelings and views of the participants (Creswell, 1994). As the study sought to ascertain the views of Pakistani men and women on IPV within marital relationships, the grounded theory approach was thought to be suitable to achieve the objective. Other approaches that were considered for this research study included Phenomenology, Interpretive Phenomenological Analysis (IPA) and Framework Analysis Approach reference these. A brief description of these approaches, and the reasons for not using each approach, are discussed here:

Phenomenology:

Phenomenology has roots in European Philosophy and was developed by Hurssel (1970) while he was studying consciousness as experienced by the participant. Phenomenological research aims to explore the lived experience of individuals to understand the construction of meaning through embodied perceptions (Sokolowski, 2000).

Phenomenological statements, like philosophical statements, state the obvious and the necessary. They tell us what we already know. They are not new information, but even if not new, they can still be important and illuminating, because we often are very confused about just such trivialities and necessities (Sokolowski, 2000, p. 57).

The approach helps understanding of lived experiences of people about a particular phenomenon of interest from the perspective of participants. The researcher using phenomenology is required to approach the data without any prejudices and pre-conceived ideas (Baker et al., 1992). Phenomenological research explores participant's personal experiences, however, the approach fails to take psychosocial and cultural influences into account and for this reason the approach was not appropriate for the present study.

Interpretive Phenomenological Analysis:

The second approach considered was interpretive phenomenological analysis (IPA). It is a relatively new approach that is inductive in nature. It has its roots in psychology and is developed and described by Smith (1996). The approach is "phenomenological in that it seeks an insider perspective on the lived experiences of individuals, and interpretative in that it acknowledges the researcher's personal beliefs and standpoint and embraces the view that understanding requires interpretation" (Fade, 2004, p. 648). Research studies based on IPA aims to explore people's personal perceptions and views about a phenomenon of interest. Like grounded theory, the approach is not based on prior assumptions and does not test hypotheses. However, the method focuses on the personal experiences and views of the participants and their psychological world (Reid et al., 2005). It does not take into account the societal and cultural influence, context and process in which the phenomenon of interests occurs, whereas, the grounded theory approach focuses on exploration of social context and processes surrounding the phenomenon of interest. For this reason this approach was not considered suitable for the present study.

Framework Analysis Approach:

The framework analysis approach is a relatively recent approach proposed by Jane Ritchie and Liz Spencer (1994). The approach was specifically developed for applied or policy related qualitative research. It is considered a generic and flexible method of qualitative data analysis rather than a highly specific technique. The method can be applied with a wide variety of qualitative data collection methods. The method is better suited to the policy related research "...that has specific question, a limited time frame, a pre-designed sample (e.g. professional participants) and a priori issue (e.g. organizational and integration issue) that need to be dealt with" (Srivastava & Thompson, 2009, p. 73). Although data analysis is conducted deductively from pre-set aims and objectives and is informed by a priori reasoning (Pope et al., 2000), this approach facilitates description and interpretation of what is occurring in a particular setting.

The approach was not considered suitable for this study as the aim and research question was very broad. In addition, the study intended to explore how people make sense of IPV. Exploration of socio-cultural and contextual factors was important in this regard as one's definition and sense of reality is based on these factors. The study required an approach which allows comparison and contrast and needed an inductive analytical approach with little a priori reasoning. In addition, the purpose of the study was to develop a theory of IPV in marital relationships in the Pakistani population. Owing to all these reasons a grounded theory approach was considered more suitable. The section below introduces the grounded theory approach, describes its various forms and discusses reasons for opting for this approach.

Grounded theory

Grounded theory is an inductive approach, based on systematic procedure to develop theory that is grounded in data (Strauss & Corbin, 1990). The focus of grounded theory is incidents and not the people. The approach tries to identify the main concern of the participants in the incidents mentioned, what concerns them, what they mean for them, and how they approach them. It is an approach that examines the process surrounding the area of interest. The approach helps build middle-range theoretical frameworks based on the collected data (Charmaz, 2000). Grounded theory was considered the most suitable approach for this study as it focuses on the social process regarding the phenomenon of interest and could help in building a theory of IPV by considering the similarities and differences in individual perspectives of the participants.

Grounded theory was developed by two sociologists, Barney Glaser and Anselm Strauss (1967), when both of them collaboratively researched dying patients and later published their book called "Awareness of Dying" (1965). They developed the method of constant comparison, which is also known as grounded theory. It is a general method that can be used with quantitative or qualitative data (Charmaz, 2000). However, as the data used for this method is text based and not number or statistics based, it is frequently considered appropriate with qualitative research (Charmaz, 2000). Over time, both researchers have chosen different paths that have resulted in a split of grounded theory methodology into Glaserian grounded theory (grounded theory based on the ideas of Glaser), and Straussian grounded theory (Grounded theory based on Strauss's concepts). Both of them have worked on many other books in the support of their own work and to promote their own version of grounded theory. The split was obvious after Strauss's publication of Qualitative Analysis for Social Scientists (1987) followed by publication of Basics of Qualitative Research: Grounded Theory Procedures and Techniques by Strauss and Juliet Corbin in 1990. Glaser responded to this with a publication titled Basics of Grounded Theory Analysis: Emergence vs. Forcing (1992), which was a chapter-by-chapter response to illuminate the difference between the two versions of grounded theory. Glaser (1992) claimed that whatever was written by Strauss was not grounded theory. Glaser believed in induction or emergence of theory, whereas Strauss was more concerned with a systematic and validating approach. Glaser also believed that the researcher should not conduct a prior literature review as it could result in preconceived ideas and would impinge the emergence of theory that is truly grounded in the data. On the other hand, Strauss advocated preliminary review of literature to improve theoretical sensitivity (Strauss & Corbin, 1998). Strauss advocated use of a paradigm approach to facilitate the theory generation process in a systematic manner, whereas Glaser believed that Strauss's approach was too prescriptive and could result in forcing categories and theory rather than facilitating emergence of theory.

Another variation of grounded theory is offered by social constructivists such as Charmaz (Charmaz, 1999, 2003, 2006) and Annells (1996). The constructivist grounded theory approach "â€¦ take[s] a reflexive stance on modes of knowing and representing studied life" (Charmaz, 2005, p. 509). This approach acknowledges the significance and effect of the researcher's prior interpretive frame, their biography, research interest, research context, researcher's relationship with research participants, "concrete field experiences, and modes of generating and recording empirical material" (Charmaz, 2005, p. 509). Charmaz identifies Glaser and Strauss as objectivist grounded theorists who believe in the existence of a single reality (Charmaz, 2000). In contrast, she proposes the constructivists believe that realities are constructed and reconstructed, as discussed earlier. According to Charmaz (2000), a constructivist approach differs from objectivist grounded theory in several ways. Firstly, unlike objectivist grounded theory, constructivist grounded theory aims to study participant's individually constructed realities and therefore do not claim to be generalisable. Secondly, it does not consider conceptual diagrams as necessary. Charmaz (2000) believes that these can hinder the depiction of a comprehensive view of process or situation. Constructivist grounded theory also considers various specific procedures such as axial coding and use of conditional matrix (Strauss & Corbin, 1998) as unnecessary, too prescriptive and positivistic. Thirdly, unlike objectivist grounded theory, constructivist grounded theory considers the researchers as co producers and authors who play an important role in construction of shared reality with the participants (Charmaz, 2006). Unlike Glaser and Strauss, Charmaz (2003) considers grounded theory on a continuum from objectivist to constructivist and believes that future lies with both. The following table summarises the main difference between the objectivist and constructivist versions of grounded theory. Charmaz (2000)

Table:

Objectivist Grounded Theory........................................Constructivist Grounded Theory

Comparisons and Contrasts

Foundational assumptions

Assumes external reality

Assumes multiple realities

Assumes discovery of data

Assumes mutual construction of data through interaction

Assumes conceptualizations arise from data

Assumes researcher construct categories

Views representation of data as unproblematic

Views representation of data as problematic, relativistic, situational and partial

Assumes the neutrality, passivity and authority of the observer

Assumes the observer's values, priorities, positions, and actions affect views

Objectives

Aims to achieve context-free generalizations

Views generalizations as partial, conditional, and situated in time, space, positions, actions and interactions

Aims to parsimonious, abstract, conceptualizations that transcend historical and situational locations

Aims for interpretive understanding of historically situated data

Specifies variables

Specifies range of variation

Aims to create theory that fits, works, has relevance, and is modifiable

Aims to create theory that has credibility, originality, resonance, and usefulness

Implications for data analysis

Views data analysis as an objective process

Acknowledges subjectivity throughout data analysis

Sees emergent categories as forming the analysis

Recognises con-construction of data shapes analysis

Sees reflexivity as one possible data source

Engages in reflexivity

Gives priority to researcher's analytic categories and voice

See and (re)represents participants' views and voices as integral to analysis

Adopted from Morse et al. 2009, p. 141

maintains that grounded theory can be adapted to suit various epistemological stances. Constructivist grounded theory is a flexible approach that provides the researcher with guidelines, principles, and strategies rather than methodological rules, recipes, or a prescriptive package (Charmaz, 2006). She maintains that the grounded theory approach provides the researcher with a 's

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Research on Positivism and Post positivism

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Disclaimer: This work has been submitted by a student. This is not an example of the work written by our professional academic writers. You can view samples of our professional work here. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.

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Toward this end, the essay is divided into three parts. The first part locates policy analysis's problems in its neopositivist methods and the technocratic orientation to which they have given rise. [1] The discussion traces the failures of the field to its understanding of the object of inquiry and its narrowly empirical approach to research.

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"Post-positivism" and the real "orthodoxy" > International Studies Association

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By casting the past of the field of international relations as "positivist," Lapid's 1989 article elides important parts of the historical discourse and thus narrows the possibilities of self-understanding in the field. When we consider, however, that his article epitomizes the critical discussion of the late 1980s and early 1990s, this assessment may not seem fair.

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Logical Positivism

(Also known as logical empiricism, logical neopositivism, neopositivism). A school of philosophy which arose in Austria and Germany during 1920s, primarily concerned with the logical analysis of scientific knowledge. Among its members were Moritz Schlick, founder of the Vienna Circle, Rudolf Carnap, the leading figure of logical positivism, Hans Reichenbach, founder of the Berlin Circle, Herbert Feigl, Philipp Frank, Kurt Grelling, Hans Hahn, Carl Gustav Hempel, Victor Kraft, Otto Neurath, Friedrich Waismann.

Logical positivists denied the soundness of metaphysics and traditional philosophy; they asserted that many philosophical problems are indeed meaningless. During 1930s the most important representatives of logical positivism emigrated to USA, where they influenced American philosophy. Until 1950s logical positivism was the leading philosophy of science; today its influence persists especially in the way of doing philosophy, in the great attention given to the analysis of scientific thought and in the definitely acquired results of the technical researches on formal logic and the theory of probability.

THE MAIN PHILOSOPHICAL TENETS OF LOGICAL POSITIVISM.

According to logical positivism, there are only two sources of knowledge: logical reasoning and empirical experience. The former is analytic a priori, while the latter is synthetic a posteriori; hence synthetic a priori does not exist.

The fundamental thesis of modern empiricism [i.e. logical positivism] consists in denying the possibility of synthetic a priori knowledge.
(H. Hahn, O. Neurath, R. Carnap, Wissenschaftliche Weltauffassung. Der Wiener Kreis, 1929).
Logical knowledge includes mathematics, which is reducible to formal logic. Empirical knowledge includes physics, biology, psychology, etc. Experience is the only judge of scientific theories; however, logical positivists were aware that scientific knowledge does not exclusively rise from the experience: scientific theories are genuine hypotheses that go beyond the limits of finite human experience.
It is not possible to establish a logically durable building on verifications [a verification is an observational statement about immediate perception], for they are already vanished when the building begins. If they were, with respect to time, at the beginning of the knowledge, then they would be logically useless. On the contrary, there is a great difference when they are at the end of the process: with their help the test is performed... From a logical point of view, nothing depends on them: they are not premises but a firm end point.
(M. Schlick, '&Uumlber das Fundament der Erkenntnis', inErkenntnis, 4, 1934).
A statement is meaningful if and only if it can be proved true or false, at least in principle, by means of the experience -- this assertion is called the verifiability principle [aka the "verifiability criterion of meanng"] . The meaning of a statement is its method of verification; that is we know the meaning of a statement if we know the conditions under which the statement is true or false.
When are we sure that the meaning of a question is clear? Obviously if and only if we are able to exactly describe the conditions in which it is possible to answer yes, or, respectively, the conditions in which it is necessary to answer with a no. The meaning of a question is thus defined only through the specification of those conditions...
The definition of the circumstances under which a statement is true is perfectlyequivalent to the definition of its meaning.
... a statement has a meaning if and only if the fact that it is true makes a verifiable difference.
(M. Schlick, 'Positivismus und Realismus' in Erkenntnis, 3, 1932).
Metaphysical statements are not empirically verifiable and are thus forbidden: they are meaningless. The only role of philosophy is the clarification of the meaning of statements and their logical interrelationships. There is no distinct "philosophical knowledge" over and above the analytic knowledge provided by the formal disciplines of logic and mathematics and the empirical knowledge provided by the sciences.
Philosophy is the activity by means of which the meaning of statements is clarified and defined.
(M. Schlick, 'Die Wende der Philosophie' in Erkenntnis, 1, 1930).
A scientific theory is an axiomatic system that obtains an empirical interpretation through appropriate statements called rules of correspondence, which establish a correlation between real objects (or real processes) and the abstract concepts of the theory. The language of a theory includes two kinds of terms: observational and theoretical. The statements of a theory are divided in two groups: analytic and synthetic. Observational terms denote objects or properties that can be directly observed or measured, while theoretical terms denote objects or properties we cannot observe or measure but we can only infer from direct observations. Analytic statements are a priori and their truth is based on the rules of the language; on the contrary, synthetic statements depend on experience, and their truth can be acknowledged only by means of the experience. This conception about the structure of scientific theories is perhaps the most durable philosophical principle of the logical positivism.
Its main points are:

the distinction between observational and theoretical terms

the distinction between synthetic and analytic statements

the distinction between theoretical axioms and rules of correspondence

the deductive nature of scientific theories

These four points are linked together. Rules of correspondence give an empirical meaning to theoretical terms and are analytic, while theoretical axioms express the observational portion of the theory and are synthetic. A theory must be a deductive system; otherwise, a formal distinction between the various kinds of sentences and terms is impossible.
The distinction between observational and theoretical terms depends on the verifiability criterion of meaning. A statement is meaningful only if it is verifiable; but, in scientific theories, there are many statements which are not verifiable -- for example, assertions dealing with quantum particles or relativistic gravitational fields. These statements are too "theoretical" for a direct test; strictly speaking, they are meaningless.

To avoid such a consequence, one could either deny that these were statements, or one could try to "reduce" the "theoretical terms" to "observational terms." The theoretical terms which belong to the abstract language of a scientific theory are explicitly definable in a restricted language whose terms describe only that which is directly observable. So a distinction between observational and theoretical terms arose. But soon Carnap realized that theoretical terms are not definable by observational ones. In a first time, he proposed a partial reducibility of theoretical to observational terms ('Testability and meaning', in Philosophy of science, 3, 1936 and 4, 1937). Later, it was supposed that all theoretical terms were removable from a scientific theory. This hypothesis was supported by two outcomes of formal logic: Craig's theorem and Ramsey statements.

Craig's theorem is an unquestionable result of formal logic. According to this theorem, it is possible to translate a scientific theory in a purely observational language without any loss of deductive power. Ramsey sentences, named after English philosopher Frank Plumpton Ramsey (1903-1930), were used by Carnap for dividing the axioms of a theory in two sets, say A and R. Set R contains only statements which contain purely observational terms and expresses the empirical portion of the theory, the "observational data." Set A consists of analytic statements and defines the meaning of theoretical terms. Given a typical scientific theory T containing both observational and theoretical terms, it is thus possible to rationally reconstruct that theory as theory T* which contains no theoretical terms, such that T and T* are equivalent with respect to all observational statements that can be deduced from the avxioms of T*.

[While the analysis of relationships between the two kinds of terms began the object of many logical and philosophical studies, the distinction itself was criticized. According to Popper all scientific concepts are theoretical, for every assertion not only entails hypotheses but also is hypothetical, that is not sure and always falsifiable. Quine ('Two dogmas of empiricism' in The Philosophical Review, 60, 1951) criticized both observational-theoretical and analytic-synthetic distinction. Hempel ('The theoretician's dilemma' in Minnesota studies in the philosophy of science, II, 1958) noted that the theory T* without theoretical terms, in spite of the equivalence (with respect to the observational language) to the original theory T, is not useful as T. In fact, from an inductive point of view, T and T* are very different. Usually the original theory T suggests certain relations between its concepts, while in T* these concepts are forbidden. The discovery of laws is almost impossible in T*, while it is a natural consequence in T. Moreover, while the number of the axioms of T usually is finite, Craig's theorem does not assure us of the existence of a theory T* with a finite number of axioms. So T* is almost useless. Theoretical terms are thus necessary in science.]

In Philosophical foundations of physics, 1966, Carnap proposed a slightly different approach to observational-theoretical distinction. Now the starting-point is the difference between empirical and theoretical laws. It is possible to directly confirm (or disprove) an empirical law, while a theoretical law can be tested only through the empirical laws that are among its consequences. Moreover, an empirical law explains facts while a theoretical law explains empirical laws. Thus there are three levels:

a) Empirical facts: these are expressed by direct "observation reports"
b) Empirical laws: Simple generalizations we can directly confirm by observation. They explain facts and are employed to predict empirical facts by deducing observation statements from laws and statements of initial conditions..
c) Theoretical laws: General principles we can use to explain empirical laws:al laws by deducing the empirical laws from such theoretical statements.
Empirical laws include only observational terms, while theoretical terms occur in theoretical laws.
The distinction between analytic and synthetic statements is another consequence of the verifiability principle and it is linked with the observational-theoretical as well as axioms-rules of correspondence distinction. According to the verifiability principle, an alleged synthetic a priori statement does not have a meaning; thus there are only two kinds of assertions: synthetic a posteriori and analytic a priori. What is the role of analytic sentences in a scientific theory? Only two possibilities are allowed: an analytic statement is a logical-mathematical theorem (thus it has no empirical significance) or it is a convention that defines the meaning of theoretical terms.

There is an explicit assumption in logical positivism's analysis of science: a theory is a deductive system. This means that pragmatic aspects are not considered. Moreover, neopositivism was not interested in the real process of discovering, but it was concerned with the rational reconstruction of scientific knowledge, that is it dealt withlogical (formal) relationships between statements in a given theory.

According to logical positivism, there is not any method of discovering a hypothesis prior to its test by deducing empirical consequences, and therefore a scientist can propose any hypothesis he prefers; only logical relationships between the hypothesis and the given empirical evidence are relevant. But there were some problems with this conception of science. First of all, the relation between empirical experience and theoretical principles is not a deductive one: observational statements do not imply theoretical axioms. Carnap argues that the relation is explicable with the help of the inductive logic.

Subsequent History of Logical Positivism:

The spread of logical positivism in USA came in the early 1930s. In 1929 and in 1932 Schlick was Visiting Professor at Stanford, while Feigl emigrated to USA in 1930, where he became lecturer (1931) and professor (1933) at the University of Iowa and afterwards at the University of Minnesota (1940). In 1932 the American Philosophical Association organized a discussion on the philosophy of logical positivism. In the same years several articles about logical positivism were published in American philosophical journals. In 1936 Schlick was murdered by a Nazi student at the University of Vienna. Between 1936 and 1940 several German and Austrian philosophers emigrated to USA: Carnap moved in 1936 to the University of Chicago, Reichenbach in 1938 to UCLA, Frank in 1938 (he became professor at Harvard University in 1939), Hempel in 1939 (City College of New York and in 1940 Queens College). Logical positivists found a favourable terrain in USA. They established solid relationships with American pragmatism; particularly Charles Morris took part to several neopositivist's projects. One of them was the International Encyclopedia of Unified Science, primarily promoted by Neurath. Although the original project was never fully realized, many works were indeed published.

The English philosopher Alfred Jules Ayer (1910-1989) played an important role in spreading logical positivism. His work Language, Truth and Logic, 1936, gained an immediate success. In that book, Ayer completely accepted both the verifiability principle and the distinction between analytic and synthetic statements; hence he asserted that metaphysical sentences are meaningless. A direct influence was exerted by Waismann and Neurath who emigrated in England in 1937 and 1940 respectively.

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Logical Positivism (Internet Encyclopedia of Philosophy)

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Logical Positivism (Also known as logical empiricism, logical neopositivism, neopositivism). A school of philosophy which arose in Austria and Germany during 1920s, primarily concerned with the logical analysis of scientific knowledge.

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The term 'logical empiricism' has no very precise boundaries and still less that distinguishes it from 'logical positivism'. It is therefore hard to map. 'Logical empiricism' here includes three groups: (1) the Vienna Circle, here taken broadly to include those who were part of various private discussion groups, especially that around Moritz Schlick, and also the members of the more public Ernst Mach Society (Verein Ernst Mach), (2) the smaller, but perhaps more influential Berlin Society for Empirical Philosophy (later called the Berlin Society for Scientific Philosophy), and (3) those influenced by or who interacted with members of the first two groups and shared an intellectual kinship with them. Besides Vienna and Berlin, there were important centers of the movement in England, France, Scandinavia, at several universities in the U.S., and even China. This characterization includes thinkers who disagreed with doctrines espoused by members of the original groups and even some who defined themselves in opposition to the movement. This results in a vague boundary, but it suffices to identify a movement in which a large number of able philosophers self-consciously participated and to distinguish logical empiricism from other movements.

It does not, however, distinguish logical empiricism from logical positivism, and it is doubtful that any principled such boundary can be drawn along doctrinal or sociological lines (Uebel 2013). Usually when distinctions are drawn, 'logical empiricism' is the wider term. Members of the Berlin group never used the term 'positivism' about themselves, but did use it concerning some unnamed Viennese in stressing their differences from the latter. In any case, these differences, even if real, were smaller than the differences within the Vienna Circle on one hand or within the Berlin group on the other. 'Positivist' is a term usually applied by opponents of various doctrines. It was used by some of the Viennese logical empiricists about themselves but generally with caution and in stressing the differences between their own views and those of the 19 th century positivists. The one philosopher who would have unhesitatingly described himself as (having been) a logical positivist was A.J. Ayer.

Another way of mapping the boundaries of logical empiricism is to list the specific philosophers who were centrally or peripherally part of it. This included many of the most important philosophers of the mid-twentieth century. Hans Hahn, Moritz Schlick, Rudolf Carnap, and Otto Neurath were leaders of the Vienna Circle, and Kurt Gödel regularly attended its meetings. The list of its members, visitors, and interlocutors is staggering, including A.J. Ayer, Herbert Feigl, Philipp Frank, Hans Hahn, Carl Hempel, Karl Menger, Richard von Mises, Ernest Nagel, Karl Popper, W.V. Quine, Frank Ramsay, Hans Reichenbach, Alfred Tarski, Friedrich Waismann, and Ludwig Wittgenstein, among many others. Not all of these would admit to being part of the logical empiricist movement, of course, but a case can be made that all contributed to it. The Berlin Society for Empirical (or Scientific) Philosophy was, as stated, smaller but perhaps more influential. Led by Hans Reichenbach, it included Kurt Grelling, Walter Dubislav, Kurt Lewin, Richard von Mises, Paul Oppenheim, and others. Hempel took his doctorate in Berlin, working with Reichenbach until the latter was forced to leave in 1933. Hempel also spent time in Vienna and Prague. Of course, among the foremost associates of the Berlin Society was Albert Einstein, who was also in Berlin also until 1933.

There was also an important group of logicians in Warsaw of which Alfred Tarski is the best known. Tarski interacted significantly with the logical empiricists in Vienna, Berlin, and the U.S., but it is more reasonable to classify the Polish logicians as an allied group rather than include them within the logical empiricist movement.

Because of the catastrophic dislocations of Europe in the 1930s, the main focus of the logical empiricism moved from central Europe to America by the close of that decade. Erkenntnis, the main journal of the movement, which had been edited by Reichenbach and Carnap, ceased publication by 1940. In 1930 Feigl moved to the U.S., and Carnap moved to Chicago in 1936. Hempel came to Chicago and Menger to Notre Dame in 1937. The ensuing years witnessed a massive exodus to America from central Europe. Reichenbach arrived in the U.S. in 1938 after five years in Turkey. Also in 1938 Gustav Bergmann and Philipp Frank emigrated. Edgar Zilsel came in 1939. Alfred Tarski was on a visit to the U.S. when Poland was invaded in 1939, and so he stayed. And by 1940 Richard von Mises was also in America.

In the U.S., these exiles were joined by the Americans Nelson Goodman, Charles Morris, W.V. Quine, Ernest Nagel, and, after the war, by Reichenbach's UCLA students Hilary Putnam and Wesley Salmon. Adolf Grünbaum can also be considered as clearly in the Reichenbach lineage. And Wilfrid Sellars was, in his early years, a close associate of Feigl. The American incarnation of the logical empiricist movement enjoyed generally good relations with the American pragmatists, not only because many of the logical empiricists had a strong pragmatist component to their philosophy, but also because the pragmatists and logical empiricists shared a common concern for empirical methodology in the service of social reform. Institutionally, the movement was represented in most major American universities, and such journals as Philosophy of Science (with Carnap and Feigl on the Editorial Board and Reichenbach and Schlick on the Advisory Board) and Philosophical Studies (founded and edited for many years by Feigl and Sellars) provided ample outlet for their publications. In addition, the Inter-Scientific Discussion Group was founded by Philipp Frank at Harvard. That grew into the Institute for the Unity of Science, called by some the Vienna Circle in exile. Meanwhile in Chicago the Encyclopedia of Unified Science was established with Neurath, Carnap, and Morris as its editors.

But even from late 30s onward the movement was hardly limited to America. Ayer remained in England. Wittgenstein returned to Cambridge in 1929, but with regular visits to Vienna, including those on which he discussed issues surrounding a strong version of verificationism with Schlick and Waismann. Popper fled to New Zealand in 1937, and in 1946 moved to the London School of Economics. Neurath fled from Vienna to the Hague and then again in 1940 to England, where he remained till his death in 1945. Friedrich Waismann went to England in 1937. In 1939 Rose Rand, a less well-known member of the Vienna Circle, fled to England and then in 1954 emigrated once more to the U.S. There were like-minded thinkers in Scandinavia (such as Jørgen Jørgensen, Eino Kaila, and Arne Naess) and as far away as Argentina (H.A. Lindemann) and China (Tscha Hung).

It is impossible to say when logical empiricism ceased to be sufficiently cohesive to be identifiable as a continuing movement. Certainly by 1960 a great many philosophers, including many who had earlier clearly been part of the movement, were identifying themselves in opposition to what they took to be logical empiricism. And some members simply changed their minds or pursued different projects. Logical empiricism probably never commanded the assent of the majority of philosophers in either Europe or America, and by 1970 the movement was pretty clearly over-though with lasting influence whether recognized or not. In the 1980s there was a resurgence of historical interest in logical empiricism. That historical interest continues to clear away many of the caricatures and misconceptions about the logical empiricists. Among the major results of this work is the recognition of the tremendous variety and subtlety of views represented within the movement and the fact that many of the arguments later deployed by critics of logical empiricism had been pioneered by the logical empiricists themselves.

Given the emphasis on science and its technical apparatus, social renewal, clarity and rationality of belief, functionality, and above all the palpable sense of doing philosophy in an importantly new way, it is reasonable to associate logical empiricism with other forms of European modernism in the 1920s and 30s, such as Neue Sachlichkeit in art and the Bauhaus in architecture and design, and with mid-century modernism as well as with political liberalism, from the New Deal to the Great Society in the United States. There have been recognizably modernist developments in various fields including philosophy for centuries.

With a movement as large and complex as logical empiricism a great many factors went into raising the questions it would address, making them seem urgent, and making it seem as though the intellectual resources it would need to address these questions were either at hand or could be developed.

One long-term process with profound implications was the steady departure of the various sciences from philosophy to form autonomous disciplines. By early in the twentieth century mathematics, physics, chemistry, biology, and the social sciences were all pursued professionally and independently from philosophy. And psychology was just separating from philosophy. Yes, there were polymaths who could and did pursue a science and philosophy professionally. Those were increasingly rare, though single-discipline scientists did from time to time make philosophic-seeming pronouncements. But they did so from outside the field. This pattern of steady departures raised the pressing question: What sort of thing remained behind? Once mathematics and the empirical sciences all left, what was left for philosophy?

The nature of philosophy was always a vexed philosophic question, but now it was particularly insistent. Surely there was no domain of empirical facts that philosophy could call its own. All that real estate had been parceled out. One answer available at the time that logical empiricism flourished was that the genuinely philosophic remainder after the departure of the sciences is somehow deeper than the empirical sciences and gets at matters, perhaps cultural ones, that are more profound and important than anything that empirical science even can address. This is either because on this conception philosophy has a mode of access or "evidence" that the empirical sciences do not and cannot have, or because the very idea of fidelity to evidence and punctilious argument is somehow small-minded.

The logical empiricists found this answer unappealing. Indeed, this conception of philosophy is precisely what Carnap means by 'metaphysics'. (As a consequence, what Carnap meant by that word is different from what late twentieth and early twenty-first century philosophers generally mean in describing their own work as analytic metaphysics.) The logical empiricists were eager to conceive of their enterprise as scientific and to engage in philosophy only insofar as it was also scientific. This science need not be empirical and need not include all that was traditional in philosophy that had not been incorporated into the independent sciences. The decision to be scientific can hardly be the end of the story. It requires rather better and more detailed answers to questions about what scientific methods are, how the mathematical (and other apparently non-empirical sciences) fit together with the empirical ones, and what, more precisely, philosophy's role was.

A second series of developments that raised questions for logical empiricism to address were developments in the sciences themselves, especially the rise of non-Euclidean geometries in mathematics and the establishment of relativity theory in physics. These posed a serious challenge to what would otherwise be an attractive scientific philosophy, namely some version of Kantianism. Kant had recognized that the best of modern science was often mathematical in character and had labored to integrate both geometry and arithmetic into our empirical picture of the world. He had held that we could not represent the world except as a Euclidean structure and hence Euclidean geometry was, a priori, a permanent feature of any future physics. The demonstration that non-Euclidean pure geometrical structures were as consistent as Euclidean ones and that spaces can indeed be represented as a non-Euclidean manifolds was one half of the problem. The other half came when Einstein argued convincingly that physical space was best described as a non-Euclidean manifold of non-constant curvature. Plainly Euclidean geometry could not be guaranteed a future physics. Modern mathematical logic also posed a problem for other Kantian claims, but not in the same wrenching way.

Many logical empiricists started out as neo-Kantians: Reichenbach, Carnap, Schlick, and even Hempel (until he studied with Reichenbach, who by that time had revised his view). The difficulties with geometry and relativity certainly do not refute all forms of neo-Kantianism, but the difficulties are quite real nonetheless. The need is to understand how mathematics can be integrated into what is otherwise an empirical enterprise, i.e., physics, chemistry, biology, etc. Addressing this need was to be a major part of the logical empiricist program.

The background of logical empiricism described so far has been confined to the academic world, but events outside that domain shaped the movement as well. World War I was an unmitigated disaster for central Europe, followed by economic turmoil in the 20s and political upheavals of the 30s. It is hard to exaggerate these changes. Monarchies that had stood for centuries disappeared overnight and their empires disintegrated. This level of political convulsion had not been seen since the French Revolution, and that earlier upheaval was comparatively confined. Cultural changes were equally profound, and these were reflected by radical departures in the arts such as painting, music, and architecture, and even more importantly in new modes of living.

The logical empiricists were no mere bystanders. They, or at least the main leaders of the movement, were politically and culturally engaged. Even more important, this engagement was accompanied by the conviction that their cultures were incapable of the necessary reform and renewal because people were in effect enslaved by unscientific, metaphysical ways of thinking. Such ways of thinking might be exemplified in theology, in the racial hatreds of the day, in conceptions of property, and in traditional ideas about the "proper" roles of men and women in society. So to articulate a "scientific world conception" and to defend it against metaphysics was not just to express an academic position in the narrow sense. It was a political act as well; it was to strike a blow for the liberation of the mind. To articulate scientific methods and a scientific conception of philosophy was the essential first step in the reform of society and in the emancipation of humankind (Carnap 1958/2017, Creath 2009, Uebel 2012.

If all of this sounds like something out of the 18 th century Enlightenment, the analogy was not lost on the logical empiricists themselves. André Carus has argued that this is exactly what Carnap had in mind by "explication" (Carus 2007). Neurath frequently drew parallels between the logical empiricists' anti-metaphysical program and the earlier Enlightenment ambitions. Certainly Kant had inveighed against the metaphysics of his time, and the anti-metaphysical tradition remained strong within the scientific community through the 19 th century.

The point so far was not to ask whether the logical empiricists were right in any of this. That question will come up later. So far the issue has been only to see the motivations that the logical empiricists had-and from their point of view-for addressing certain questions and for thinking that answers to those questions were urgently needed. None of this, however, says why the logical empiricists thought they had or could have the means to answer these questions. To that we now turn.

Since Newton the most paradigmatic examples of empirical science were those claims, usually quantitative ones, that were properly inferred from or appropriately confirmed by experience. Speaking very informally, these are the ones that we have good reason to believe or at least better reason to believe than the available alternatives. The problem, of course, is to specify the form of proper inferences, the form of an appropriate confirmation relation, and/or the structure of good reasons. The task is daunting, but logic in a suitably broad sense seems to be the right tool. Still speaking informally, logic seems to give us the structure of (good) reasoning. There are other conceptions of logic, of course, but this is a standard one and pretty well describes what the movement needed.

If logic was the tool that was wanted, it was newly ready for service. The progress of modern mathematical logic from Bolzano through Russell and beyond was truly impressive. Arguably, it could now express all parts of classical mathematics. Besides the first order predicate calculus one would need either set theory or higher order logic, but these were recent developments as well. Logic, like the empirical sciences, was progressive and could be approached cooperatively by more than one investigator. In Our Knowledge of the External World (1914) Russell had even positioned logic as the locus of scientific method in philosophy. It is small wonder then that those who were looking for something scientific in what was left of philosophy turned to logic. Wittgenstein's no-content theory of logic in the Tractatus (1921/1922) was tantalizingly suggestive about how mathematics could be integrated into an overall empirical theory of the world. Wittgenstein also expressed a radical verificationism in the early 1930s in his conversations with Schlick, Waismann, and other members of the Vienna Circle. Many of the logical empiricists in turn could see in some version of that verificationism the ideal tool with which to carry out their anti-metaphysical program. There was, naturally, much left to accomplish, but even with Gödel's results one could expect that further impressive strides in logic could be made. Indeed, much was accomplished even if the perfect account of scientific reasoning proved elusive. Perfection is elusive in all the sciences, but that is no reason for despair.

The logical empiricist movement is the sum of the interwoven trajectories of its members, so one way of describing that movement is to trace those various trajectories. To do so in detail for all those involved would take rather longer than the movement lasted. That would be inappropriate for one entry in an encyclopedia, especially one in which entries for many of the members will appear independently. The thumbnail sketches of the work of some representative figures below show the breadth and international character of the movement. While the list is long, it covers only a small fraction of those involved and leaves out many important thinkers.

A.J. Ayer (1910-1989)

An English philosopher in the tradition of British empiricism, Ayer visited the Vienna Circle in 1932-33. His book Language, Truth, and Logic (1936) was a best seller after World War II and represents logical positivism to many English speakers

Rudolf Carnap (1891-1970)

German by birth, he taught in Vienna, Prague, Chicago, and Los Angeles. He was one of the leaders of the Vienna Circle and of logical empiricism, especially of those within the movement whose formulations were more liberal, e.g., with respect to the criterion of verification. He defended logical and methodological pluralism and worked to develop an epistemic approach to probability.

Walter Dubislav (1895-1937)

A German logician and philosopher of science, Dubislav was one of the founders, with Reichenbach and Grelling, of the Berlin Society of Empirical (later Scientific) Philosophy.

Herbert Feigl (1902-1988)

Born in what is now the Czech Republic, Feigl studied in Vienna with Schlick and Hahn. He emigrated to the U.S. before most other logical empiricists would do so. He taught at the Universities of Iowa and Minnesota and founded both Philosophical Studies, with Wilfrid Sellars, and the Minnesota Center for the Philosophy of Science. He is best known for his work on the mind-body problem.

Philipp Frank (1884-1966)

This Viennese physicist and philosopher of science taught at Vienna, Prague, and Harvard. He was part of a discussion group with Hahn, Neurath, and others that preceded the Vienna Circle. At Harvard he founded the Inter-Scientific Discussion Group that developed into the Institute for the Unity of Science. He was also one of the founders of the Boston Colloquium in the Philosophy of Science.

Kurt Gödel (1906-1978)

Born in what is now Slovakia, Gödel took his doctorate under Hahn in Vienna, studying with Carnap and Schlick as well. He also regularly attended Vienna Circle meetings and taught in Vienna. The bulk of his career was spent at the Institute for Advanced Study at Princeton. He is best known for his spectacular incompleteness theorems, and his Platonist orientation toward mathematics. Though a participant in the logical empiricist movement during the Vienna years, Gödel thought that Carnap's approach to mathematics could be refuted. The alleged proof (Gödel 1995) was not published in Gödel's lifetime and remains controversial.

Kurt Grelling (1886-1942)

Grelling was born in Berlin and took his doctorate in Göttingen under Hilbert. With Leonard Nelson he developed a famous semantic paradox that bears their names. He was one of the founders of the Berlin Society for Empirical (later Scientific) Philosophy. Grelling died in the Holocaust because for bureaucratic and political reasons news of an academic appointment in the U.S. reached him too late.

Adolf Grünbaum (1923-)

Grünbaum moved from his native Germany as a teenager, studied under Hempel at Yale, and spent the bulk of his career at the University of Pittsburgh, where he founded the Center for Philosophy of Science. The major themes of his work have been philosophy of space and time, rationality, and psychoanalysis.

Hans Hahn (1879-1934)

Hahn, a distinguished mathematician, took his doctorate in his native Vienna in 1902 and began teaching there in 1905. He was part of a group with Frank, Neurath and others that discussed logical and methodological issues prior to World War I. After teaching at Czernowitz (now in Ukraine) and Bonn he was given a chair in mathematics at Vienna in 1921. He was instrumental in bringing Schlick there in 1922 and so was called by Frank "the actual founder of the Vienna Circle" (Stadler 1997/2001, 642). His most famous student was Gödel.

Olaf Helmer (1910-2011)

Helmer took a doctorate in his native Berlin under Reichenbach and a second doctorate under Susan Stebbing in London. He collaborated with other logically minded philosophers. Indeed, the team of Hempel, Helmer, and Oppenheim became known as "H₂O". The bulk of his career was spent at the Rand Corporation.

Carl G. Hempel (1905-1997)

Born just north of Berlin, Hempel studied at both Göttingen and Berlin. Most of his doctoral work was completed under Reichenbach when the latter was forced to leave Germany. Hempel taught at a number of American universities, most famously at Princeton and the University of Pittsburgh. He was the doctor father of many prominent philosophers of science, and his work focused on confirmation, explanation, and concept formation.

Richard Jeffrey (1926-2002)

This American logician and philosopher of science earned an MA with Carnap (with whom he later collaborated) and a PhD with Hempel (with whom he was for many years a colleague and close friend at Princeton). He developed Jeffrey conditionalization (see below) and defended probabilism.

Kurt Lewin (1890-1947)

Born in what is now Poland, Lewin took his doctorate in Berlin in 1916. He lectured there in both philosophy and psychology until 1933 when he emigrated to the U.S. via England. Thereafter he taught at a number of American universities including Cornell, Iowa, MIT, and Duke. Credited with founding modern social psychology, he laid the foundations for what is now called sensitivity training as a way to combat religious and racial prejudices.

Richard von Mises (1883-1953)

Born in what is now Ukraine, Richard von Mises is the brother of the economic and political theorist Ludwig von Mises. Richard was a polymath who ranged over fields as diverse as mathematics, aerodynamics, philosophy, and Rilke's poetry. He finished his doctorate in Vienna. He was simultaneously active in Berlin, where he was one of the developers of the frequency theory of probability along with Reichenbach, and in Vienna, where he participated in various discussion groups that constituted the Vienna Circle. Eventually it was necessary to escape, first to Turkey, and eventually to MIT and Harvard.

Charles W. Morris (1901-1979)

Morris was an American pragmatist and philosopher of language at the University of Chicago when Carnap arrived there. These two, together with Neurath until the latter's death, were the chief editors of the Encyclopedia of Unified Science. After Carnap left Chicago, Morris moved to the University of Florida.

Otto Neurath (1882-1945)

This Austrian philosopher of science and sociologist took his doctorate in political science in Berlin. A member of the First Vienna Circle and a leader of the "left" wing of the Vienna Circle, he was also politically active. He was a significant museum director, and as part of this developed the ISOTYPE picture language. His main philosophic themes were physicalism, anti-metaphysics, and the unity of science. He was the Editor-in-Chief of the Encyclopedia of Unified Science until his death. Eventually he fled to the Netherlands and from there to England.

Paul Oppenheim (1885-1977)

A successful industrialist and heir to a substantial fortune, Oppenheim was trained in his native Germany in chemistry and philosophy. He was a close friend of Einstein, and helped to initiate the Berlin Society for Empirical Philosophy. Oppenheim collaborated with many important logicians and philosophers of science both in Europe and the U.S. He also helped many to escape Nazi oppression, and continued to help in a variety of ways even after he settled in Princeton in 1939.

Karl Popper (1902-1994)

Born in Vienna and with a doctorate there, Popper was intensely engaged in discussions with members of the Vienna Circle. His main philosophical work, The Logic of Scientific Discovery (1935/1959), appeared in a series edited by Schlick and P. Frank. He did not however, regularly attend meetings of the Vienna Circle and generally considered himself an outsider. Later he claimed to have "killed" logical positivism. From Austria Popper escaped to New Zealand and eventually to the London School of Economics, where he was knighted for his political writings.

Hilary Putnam (1926-2016)

This American philosopher of science, mathematics, mind and language earned his doctorate under Reichenbach at UCLA and subsequently taught at Princeton, MIT, and Harvard. He was originally a metaphysical realist, but then argued forcefully against it. He has continued the pragmatist tradition and been politically active, especially in the 1960s and 70s.

W.V.O. Quine (1908-2000)

Born in the U.S., Quine took his doctorate and spent his entire career at Harvard. In 1932-33 he visited the Vienna Circle and then Carnap and Warsaw. For the next six years, he said, he was a disciple of Carnap's and even after they began to disagree, Carnap set the agenda. Eventually they clashed over analyticity, modality, and intensional contexts generally. Many similarities of view with Neurath are apparent, especially on the issues of holism, underdetermination, and naturalism in epistemology.

Hans Reichenbach (1891-1953)

Reichenbach was born in Hamburg and, after immersing himself in mathematics, physics, and philosophy, took his doctorate in Erlangen, Germany. He was a founder and the leader for the Berlin Society for Empirical (later Scientific) Philosophy. In 1933 he was forced to leave Berlin. He went to Turkey and then in 1938 to UCLA. Among his many students were Hempel, Putnam, and W. Salmon, and so almost all philosophy of science in the U.S. can trace its academic lineage to Reichenbach. Though interested in social and educational reform, he worked primarily in philosophy of physics. He developed and defended a frequency theory of probability, and emphasized both scientific realism and the importance of causality and causal laws.

Wesley Salmon (1925-2001)

Salmon was born in Detroit and, after an initial interest in theology, earned his PhD under Reichenbach at UCLA. He taught at a number of universities including Brown, Indiana, Arizona, and Pittsburgh. His interests centered on causality and explanation, and his statistical relevance model of explanation can be thought of as addressing and in large measure resolving the problem of the single case in frequency theories of probability.

Moritz Schlick (1882-1936)

Schlick was born in Berlin and eventually took his doctorate there in mathematical physics under Max Planck. He taught at a number of German universities before he was, at the instigation of Hans Hahn, called to the Chair in the Philosophy of the Inductive Sciences at Vienna, a chair that was previously held by Boltzmann and Mach. Schlick was one of the first philosophers to write about Einstein's relativity theory. He was close to Wittgenstein and one of the conduits for the latter's strict verificationism. His work ranges from space and time to general epistemology and ethics. In 1936 he was assassinated on the steps of the university by a deranged student.

Wilfrid Sellars (1912-1989)

Wilfrid Sellars was the son of well-known philosopher, Roy Wood Sellars. Wilfrid studied at Buffalo, Oxford, and Harvard before teaching at Iowa, Minnesota, Yale, and Pittsburgh. He was a close associate and collaborator with Feigl at Minnesota. (He once said that he and Feigl were for years discrete parts of a single entity.) He defended scientific realism, pragmatism, and naturalism, and his philosophy of language drew heavily on Carnap's Logical Syntax (1934/1937)

Alfred Tarski (1901-1983)

Born and educated in Warsaw, Tarski earned his doctorate under Lesniewski. He happened to be visiting the U.S. when Poland was invaded and so avoided the fate of so many of his colleagues. He taught at the University of California at Berkeley for more than 30 years. While it is unclear whether he should be counted as a logical empiricist, he visited the Vienna Circle and hosted its members in Warsaw, and his "The Concept of Truth in Formalized Languages" (1936/1956) was very influential on Carnap and on the development of semantics among the logical empiricists generally.

Friedrich Waismann (1896-1959)

Waismann was born in Vienna and earned his doctorate there under the direction of Schlick in 1936. From 1926 to 1933 he held discussions with Wittgenstein, generally in the company of Schlick, but also sometimes Carnap or Feigl. Waismann kept detailed minutes of these conversations. At one point he and Wittgenstein contemplated a joint book, but Wittgenstein later changed his mind. Besides the printed text of the Tractatus these conversations were the main conduit of Wittgenstein's ideas into the Vienna Circle. In 1937 Waismann was able to emigrate to England. After a couple of years at Cambridge, where he was shunned by Wittgenstein, he moved to Oxford, where he taught until his death.

Ludwig Wittgenstein (1889-1951)

Born into an immensely wealthy Viennese family, Wittgenstein studied at Cambridge from 1911, where he formed friendships with Russell, Keynes, and Moore. His Tractatus Logico-Philosophicus (1921/1922), which among other things tries to show that logic has no content, was enormously influential on many logical empiricists. Wittgenstein continued to spend much of his time in Austria working variously as an elementary school teacher, a gardener, and as an architect of a house for his sister in Vienna. While there he held influential discussions with Schlick, Waismann, and others. From 1930 he held teaching posts at Cambridge and increasingly distanced himself from the logical empiricists. His later work focused on ordinary language and inspired many other philosophers as well.

It is not possible in an essay of this scope to trace all the issues that the logical empiricists addressed or even to treat any one of them with completeness. What is possible is to highlight some salient issues, clear away some misconceptions about them, and sketch a bit how those issues were developed over time. The first is a related set of concerns: empiricism, verificationism, and anti-metaphysics. The second is the logical empiricists' treatment of logic and mathematics as analytic. Third is the related issues of the unity of science and reduction. And finally, comes the issue of probability. Given what has already been said, the reader should be aware that none of the doctrines discussed below was shared by all members of the logical empiricist movement.

Since antiquity the idea that natural science rests importantly on experience has been non-controversial. The only real questions about the sources of scientific knowledge are: Are there parts of science that do not rest on experience or rest also on something other than experience? If so what account can we give of those parts? And to the extent that science does rest on experience how can we know that it does? There is another question about science related to these, though not strictly about the sources of science, and that is: Why, in making claims about the world, should we be scientific as opposed to say mystical? The difficulty is that any scientific answer to this last question would reasonably be thought to beg the very question it purports to address.

Long before the twentieth century the prevailing opinion was that Euclidean geometry, standard mathematics, and logic did not rest on experience in any obvious way. They were largely presupposed in our empirical work, and it was difficult to see what if anything might disconfirm them. Geometry was a special case and might be handled in different ways that we shall not discuss here. That leaves logic and mathematics.

If Frege and Russell were right, then mathematics could be thought of as expressing no more than logical truths and handled in whatever way logic was to be treated. For Frege both mathematics and logic were analytic, but that, even if true, does not provide the needed answers. Wittgenstein's no-content theory of logic suggested that all of the real claims, the ones that had genuine content, could be appropriately supported by experience, and the logical and hence mathematical claims had no content to support. This seemed to open the way for a thoroughgoing empiricism in which the logical and mathematical fit in with the ordinary claims of physics and biology in a harmonious way. The next subsection about analyticity discusses the question of whether the needed distinctions can be drawn.

In developing his theory of types Russell said in effect that some expressions that seem to be sentences in fact say nothing at all. This is because, despite appearances, they are not grammatically well formed. Wittgenstein found this suggestive. In the Tractatus he suggested that much else was nonsense as well including traditional metaphysics and supposed claims about the "higher". When in late 1929 Wittgenstein proposed (Waismann 1967/1979), in conversations with Schlick and Waismann, a strict verificationism as a basis for identifying the legitimate parts of discourse, this seemed to the logical empiricists to be a very attractive tool for setting aside the unscientific parts of philosophy.

This does not mean, however, that all logical empiricists or even all members of the Vienna Circle accepted the strict verificationist view that in order to be meaningful a claim must be implied by a finite number of observation sentences. Even though those observation sentences need not be true, this view had the drawback that so-called laws of nature would not be meaningful on this criterion. Schlick was prepared to bite the bullet and hold that laws were not statements at all but principles of inference. Others were not prepared to go so far and sought more liberal formulations. This more liberal or "left" wing of the Vienna Circle included Carnap, Philipp Frank, Hahn, and Neurath. Carnap does not seem to have been a strict verificationist even in the Aufbau (1928/1967).

Over the years a great many different formulations of verificationist principles ensued. Most of them came to a bad end rather quickly, and this is sometimes taken as a convincing argument that any form of verificationism is utterly misguided. Perhaps, but we should be cautious. There are undoubtedly many different features joined in any one of the proposals, and even a sequence of failures may not show where to place the blame. The central idea behind verificationism is linking some sort of meaningfulness with (in principle) confirmation, at least for synthetic sentences. The actual formulations embodied not only such a link but various particular accounts of confirmation as well. Now confirmation is a complex matter, and it is unlikely that we shall have the final satisfactory account any time soon. This should not persuade us, however, that there are no satisfactory accounts of confirmation any more than our current lack of the final physics should convince us that there are no physical facts of the matter. So even a string of failures in formulating verificationist principles may mean no more than that the embedded accounts of confirmation are too simple but the link between meaningfulness and confirmation is nevertheless sound.

Even if we set this caution aside, there may be parts of persistently employed strategy that lead to persistent failure. These parts and failures might be avoidable. To see how this may be so we will compare what is perhaps the most famous formulation of the verificationist principle, in Ayer 1936, with a later one, in Carnap 1956. A.J. Ayer had visited the Vienna Circle from late 1932 on into 1933, returning home for the summer term. While in Vienna he attended meetings of the Circle and overlapped for five weeks with Quine. Neither Carnap nor Neurath were there at the time, so the left wing of the Circle was not fully represented. When Ayer returned to England he published Language, Truth, and Logic in 1936. Even immediately it was widely discussed, and after the war sales were spectacular. For many in England this book was the epitome of logical positivism and remains so.

Ayer was careful to restrict his criterion of meaningfulness to synthetic sentences and to demand only in principle confirmation. And the formulation seems very natural: Confirmation is a feature that applies to sentences (or groups of them) and not to sub-sentential parts, and for an empiricist the content that a synthetic sentence has would be empirical content. So it would seem that to have empirical content a sentence, A, should either directly imply some observational sentence or add to the observational content of some other sentence, B. That is, the conjunction of A and B should imply some observational sentence not implied by B alone. This formulation may be natural, but it is also fatally flawed. It would declare any sentence whatsoever as meaningful: For any sentence A and any observation sentence O, A would be meaningful because it could be conjoined to A ⊃ O. The latter would not in general imply O, but the conjunction would.

Other more elaborate formulations followed along the same lines, and other more elaborate counterexamples appeared just as fast. Hempel reviewed the situation twice within about a year (Hempel 1950 and 1951). First he concluded that it was a lively and promising line of research and later concluded that it was not promising at all. In retrospect it may be that the problems arise because we were led by the fact that confirmation is a feature that applies to whole sentences into thinking that the level at which to apply the criterion was the level of whole sentences. Now a sentence with meaningless parts might well pass some test especially if the test involves its being combined with other sentences that can have meaningless parts. So one way to avoid this difficulty is to try to find a formulation that applies the test at the level of basic expressions, those that can be thought of as "not having parts" so to speak.

This is the strategy that Carnap employed in "The Methodological Character of Theoretical Concepts" (1956). Observational terms are assumed to have empirical content. Logical terms are assumed to have none. And all defined terms are assumed to be replaced by their definitions. If for some basic, non-logical term there is a sentence that contains that term as its only non-logical element and if that sentence implies some observation sentence, then that sentence has empirical content and so does its only non-logical term. If we have established that each term from some set, K, is empirically significant we might test still further terms by seeing whether those further terms can add to what is sayable with terms from K. Carnap's actual definition is quite complicated, but it does seem to avoid the difficulties of its predecessors. It also allows an account of why those predecessors ran into trouble, viz., that they applied at the level of whole sentences (naturally enough) rather than to elementary terms.

Not long after Carnap's definition was published David Kaplan devised what seemed to be counterexamples. They became fairly well known, but they were not published until 1975. Shortly thereafter it was shown (Creath 1976) that either Carnap's definition is not open to the counterexamples as presented or it can be patched in a very natural way so that it avoids them. This does not show that there are no counterexamples or that there are no other features of the definition to which one might object. But it does show that the situation is not as dire as Hempel supposed in 1951.

We need to address another issue in considering verificationism, the persistent criticism that it is self-undercutting. The argument for this claim goes like this: The principle claims that every meaningful sentence is either analytic or verifiable. Well, the principle itself is surely not analytic; we understand the meanings of the words in it perfectly well because we understand our own language. And we still do not think it true, so it cannot be true in virtue of meaning. And it is not verifiable either (whatever we choose 'verifiable' to mean).

This sounds more compelling than it is. Ayer understood the principle to be a definition, defining a technical term, 'meaning'. If so, then the sentence expressing the principle would indeed be analytic. So the self-undercutting charge strictly fails. But so construed and with nothing else said about it the principle would not have the same punch as before. Why should a metaphysician care whether his or her utterances lack some technical feature?

Carnap explicitly takes up the "self-undercutting" charge against verifiability in Philosophy and Logical Syntax (1935), and he is not interested in introducing a new technical term, 'meaning', so or in denying this new technical property to unverifiable sentences. Carnap is careful to distinguish the language for which the verifiability principle is given from the meta-language in which we talk about that language. This meta-language would be the language in which the principle would be expressed. This may seem to offer another strategy against the "self-undercutting" charge because the principle applies to a different language than that in which it is expressed. This is not Carnap's strategy. Carnap fully understands that if the general verificationist strategy is followed, there will also be a verificationist principle expressed in the meta-meta-language governing the meta-language.

Carnap's real defense of the principle was achieved by changing the nature of the discussion. By 1935 Carnap had introduced an important new element into his philosophy called the Principle of Tolerance. Tolerance is a radical idea. There is no uniquely correct logic (1934/1937 xiv-xv). Empiricism is a convention (Carnap, 1936/1937 33). Perhaps more precisely each of the various versions of empiricism (including some sort of verificationism) is best understood as a proposal for structuring the language of science. Before tolerance, both empiricism and verificationism are announced as if they are simply correct. Correspondingly, what Carnap called metaphysics is then treated as though it is, as a matter of brute fact, unintelligible. But what is announced thus dogmatically can be rejected equally dogmatically. Once tolerance is in place, alternative philosophic positions, including metaphysical ones, are construed as alternative proposals for structuring the language of science.

None of them is the uniquely correct one, and no theoretical argument or evidence can show that it is. Nor can theoretical arguments or evidence show that it is false. Neither proposals nor languages are the sort of thing to be true or false. Instead, proposals call for practical decisions and practical arguments rather than for theoretical reasons or evidence. Carnap believes that there are indeed very good practical reasons for adopting the proposal of verificationism, for choosing a language of science in which all substantive (synthetic) claims can, at least in principle, be brought before the court of public experience. The reason is that if we do not require this, the result is "wearisome controversies" that there is no hope of resolving. That, he thinks, is the sad history of attempts to get beyond science, and it is just too painful.

If the proposals constituting some version of verificationism are adopted, then in the language thus constituted it will be analytically true that there are no synthetic sentences that are both unverifiable and meaningful. The notion of meaning here is not some new technical invention. Rather, 'meaning' is used in something like the ordinary sense. No grammatically well-formed sentence of this new language violates the verifiability principle. And the principle itself is completely safe.

Thought of in this way the verifiability principle does not describe natural language, it is not intended to. It is intended to reform language to make it a more useful tool for the purposes of science. Carnap is under no illusion that natural languages are free from metaphysics. Nor is he under the illusion that defenders of the sort of metaphysics he targets will readily step up to the challenge of presenting precise rules of grammar and inference.

There is one other change that tolerance brings to Carnap's own vocabulary. Before tolerance, verificationism is stated in such a way that violations would count only as unintelligible gibberish. With tolerance in place, Carnap is prepared to imagine non-empiricist languages, though of course he thinks they are very unwise. So instead of saying that sentences in non-empiricist languages are meaningless, he says that they are empirically meaningless. And that has a very different flavor. There is no weakening of his defense of empiricism, but it is put on a somewhat different footing.

Logic, mathematics, and mathematical geometry had traditionally seemed to be confirmationally "different". Indeed it is hard to indicate any conditions under which any parts of them would be disconfirmed. Leibniz had called them truths of reason. Hume said that they represented relations of ideas. Kant had held that the truths in these areas were a priori. Mathematics and geometry were not analytic for Kant, but logic was. Kant had two criteria of analyticity, apparently thinking them equivalent. First, in subject-predicate sentences, an analytic sentence is one in which the concept of the predicate is contained in that of the subject. Second, an analytic sentence is one whose denial is self-contradictory. This seems to include not only the sentences whose surface logical form would be of the required sort but also those that can be got from such logical truths by making substitutions that were conceptually equivalent. The more modern rough analog of this is to say that the analytic sentences are those that are true in virtue of logic and definition.

Frege certainly developed logic beyond that which was available to Kant, but he did not think of himself as changing the analytic status of it. Logic is after all the only avenue we have for giving meaning to the notion of (logical) contradiction. Of course Frege also attempted to reduce mathematics to logic (including both first and second order logic), and insofar as that reduction was successful it would have implied that mathematics was analytic as well. Frege said little of geometry, but for him it was synthetic a priori.

Carnap had not only studied with Frege, but like many of the logical empiricists he had started out as a neo-Kantian as well. So especially in view of Russell's relatively more successful attempt at reducing mathematics to logic, it was perhaps natural that Carnap would consider both mathematics and logic as analytic. Geometry could be handled in several different ways that we will not discuss here. But from fairly early on there was widespread agreement among the logical empiricists that there was no synthetic a priori, and that logic and mathematics and perhaps much else that seemed impervious to empirical disconfirmation should be thought of as analytic. The point of drawing the analytic-synthetic distinction, then, is not to divide the body of scientific truths or to divide philosophy from science, but to show how to integrate them into a natural scientific whole. Along the way the distinction clarifies which inferences are to be taken as legitimate and which are not. If, as Carnap and Neurath were, you are impressed by Duhemian arguments to the effect that generally claims must be combined in order to test them, the analytic-synthetic distinction allows you to clarify which combinations of claims are testable.

If analytic, a sentence is true in virtue of the conventions of language. In saying that, however, we must pause to confront two widespread confusions. First, Quine alleges (1963, 385f) that the notion of analyticity was developed and purports to explain for both Kant and Carnap how certainty is possible. In fact certainty has little or nothing to do with analyticity for the leading logical empiricists. In saying that such claims are based on convention they were explicitly calling attention to the revisability of conventions and the sentences that owed their meanings to those conventions. Second, nowadays any talk of convention is likely to prompt the response: "But that cannot be! No proposition can be made true by our conventions or decisions." Unless it is a proposition about conventions, this second sentence of the response is true. But it is also completely irrelevant. Analyticity applies to sentences rather than propositions. Our conventions and decisions can and do affect what expressions mean and thus what sentences mean. Once the meaning is specified, it may well be that any sentence that has this meaning would be true even if, for example, the point masses of the universe were arranged quite otherwise than they in fact are. These are the analytic sentences. No claim is being made that meaning causes anything or that convention makes anything true. The "making" image here is out of place. It is just that in these cases the truth value of the sentence may well be functionally dependent on meaning alone. If it is, then in this special sense, truth value depends on meaning, and that depends on convention. Other sentences whose meanings are specified might well be true or false depending on how things in the external world, so to speak, are arranged. In this other category of sentence the truth value is not functionally dependent on meaning alone. They are the synthetic sentences. Now this puts matters extremely informally. But at least the nature of the confusions over certainty and convention should be clear.

In the Logical Syntax of Language (1934/1937) Carnap defined 'analytic' in a new way in order to circumvent Gödel's incompleteness results. The method used was to distinguish between a derivation relation (the relation that holds between some premises and what can be got from them in a finite number of steps) and a consequence relation. The latter is an essentially semantic relation that holds between some premises and some other claim such that on all valuations under which the premises are all true, so is that other claim. This definition bears a stronger resemblance to Tarski's account in (Tarski 1936b/1956). In any case, Carnap is able to show that for any sentence of pure mathematics either it or its negation is a consequence of the null set of premises. This leaves Gödel's results completely intact as they concerned what is provable, that is, derivable from the null set of premises or from any one consistent axiomatization of mathematical truths.

As noted above, another innovation of Logical Syntax is the Principle of Tolerance. While it reflects a long-standing attitude on Carnap's part, the principle itself is new. Later Carnap was to say that the Principle of Tolerance was "perhaps better called the principle of conventionality" (Carnap 1942, 247), that is, the conventionality of linguistic forms. Tolerance stabilizes the verification principle as well as Carnap's empiricism, and it reinforces the idea that the analytic-synthetic distinction is always relative to a particular language (Creath 2009).

In the late 1950s Carnap began exploring (1963a and 1966) how a notion of analyticity might be developed for novel theoretical terms where the theories in which those terms are embedded are presented by means of a system of postulates. It is not clear that the account he developed was intended to supersede his earlier account. In any case Carnap's suggestion is as follows (where for convenience terms are used autonymously): Let T be the totality of theoretical postulates, and C be the totality of mixed sentences (the sentences of the theory containing both antecedent and novel terms). Also let R( TC) be the Ramsey sentence for TC, that is, the result of replacing each of the non-observational terms in TC with predicate variables and closing that open sentence with corresponding existential quantifiers. R( TC) ⊃ TC can, Carnap says, be thought of as the analytic sentence for the theory, that is, a sentence that gives to the theoretical terms of TC their meaning. Over the last decade, this idea of Carnap's has provoked considerable discussion that has not yet been resolved. Whatever worries there may be concerning this part of Carnap's view, they are distinct from the more famous concerns raised by Quine.

Quine began having doubts about analyticity about 1940, though he seems not to have been firmly committed against it until later. In any case his doubts were not published until 1951 in his famous paper "Two Dogmas of Empiricism". Quine's readers have understood his arguments in many different ways. The most general form of his complaint is that 'analytic' so far lacks the appropriate tie to observational criteria that Carnap's own account of theoretical terms in empirical science would demand. More specifically, where there has been an attempt at such a general criterion it has resulted in either a "drastic failure as tended to admit all or no sentences as analytic, or there has been a circularity" (Quine 1963, 404) of a kind that defines 'analytic' in terms that themselves lack the appropriate empirical criteria and so can be accounted for only by appeal to analyticity itself.

This complaint falls far short, as Quine well understood, of a proof that Carnap's appeal to analyticity was doomed. First, it relies on the demand that theoretical terms must satisfy some empirical significance criterion. Many people at the time, including some who followed Quine in rejecting analyticity, also rejected any general empirical significance demand for theoretical terms. Second, one could accept the demand for theoretical terms in physics or chemistry and deny, as Carnap did, that the demand applied to his own work. This is because Carnap saw himself as working in an area within metamathematics rather than in empirical linguistics. Third, Quine did not pretend to have considered all of the possibilities for the explication of analyticity. And so it may be possible to meet Quine's demands to the extent that they are legitimate. Fourth and finally, Quine seems in Roots of Reference (1974) to have provided an explication for 'analytic' that meets his demand for empirical/behavioral criteria without inducing either the drastic failure or the circularity envisioned above.

There is another somewhat independent thrust to Quine's campaign against analyticity. In the last section of "Two Dogmas" (1951) Quine gives an extremely attractive sketch for an alternative epistemology that apparently makes no appeal to analyticity. Insofar as that sketch can be filled out successfully it would constitute a dispensability argument against analyticity. Whether it can be thus filled out, however, remains to be seen.

Quine's other provocative theses, including especially his claims about the indeterminacy of translation, while relevant to his assessment of analyticity, would carry us too far afield to consider their ramifications here. As with most topics in philosophy there is no uniform agreement in the literature as to whether the notion of analyticity is or can be made sufficiently clear for use in scientific philosophy. Nor is there such agreement that Quine's epistemological sketch can be satisfactorily filled out. Both approaches have their defenders and their detractors. But between them they seem to be the most promising avenues for integrating the logic-mathematical part of science with the more straightforwardly empirical parts. Since Carnap is and Quine can be argued to be within the logical empiricist tradition, this progress toward such unification can be counted as part of the legacy of the movement.

The commitment of some of the logical empiricists to the unity of science has been in recent years often discussed but less often understood. One hears in conversation that it was a sort of rearguard action designed to preserve as much as possible of a phenomenalist version of ontological reduction. One reads in print that it can be refuted by the obvious fact that the various sciences have quite distinct theoretical vocabularies (Suppes 1978). Both reactions are misplaced.

It was the left wing of the Vienna Circle, and above all Otto Neurath, that championed the unity of science. They also promoted physicalism, anti-foundationalism, and a generally naturalistic viewpoint. A main focus of their activities from the late 30s was The Encyclopedia of Unified Science edited by Neurath in Europe and Carnap and Charles Morris in Chicago. A great many philosophers of many different persuasions participated in that project. The project may have been unified science, but they did not have a completely unified view of what that project was. Here we will discuss the Neurath and Carnap versions of it to see what their central concerns were.

Neurath seems to have had two primary motivations to advance under the banner of the unity of science. First, he was concerned that there be no a priori methodological cleavage between the natural and the social sciences. On the social scientific side he was concerned that these sciences not condone some private, mysterious mode of insight (empathy) whose results could not be checked against more ordinary public observation. Such a methodology would be a harbor for metaphysics. On the natural scientific side, he was concerned to point out that, for Duhemian and other reasons, the situation is much messier than is sometimes supposed, and so invidious comparisons by natural scientists at the expense of social science were unwarranted.

Second, because Neurath was socially and politically engaged he was concerned that the various sciences be connected in such a way that they could be used together to solve complex human and social problems. For this, considerable overlap of vocabulary was needed, and this he called a "universal jargon".

In recent years it is sometimes claimed that Neurath meant by the unity of science what some contemporary philosophers have defended as the disunity of science. One cannot rule this claim out a priori. But the often substantial differences among the current defenses of disunity make evaluating this claim difficult. It is fair to say, however, that Neurath was suspicious of grand hypotheses, familiar since the 19 th century to derive all of chemistry, biology, psychology, and the social sciences (in that order) from a few basic principles of physics. It is unclear whether this stems from a general opposition to system building, since he was eager to develop inferential connections among the various sciences. Perhaps this is better expressed as an opposition to speculative system building and to the idea that there is only one way of systematizing our science than to systematicity as such.

Carnap's position on unity is different from Neurath's, but they overlap. Carnap distinguished the unity of the language of science from the unity of the laws of science. He wanted to defend the former and to say what would be required for the latter. As far as the unity of the language of science, Carnap did in the Aufbau try to initiate a program for defining all of scientific concepts on the basis of a very small number of basic concepts, perhaps only one basic concept. That does afford a certain conceptual economy, but it is now generally held by Carnap scholars (see especially Friedman 1987 and Richardson 1998) that ontological reduction and reduction to a phenomenalist basis was far from his motive. Carnap explicitly acknowledged that another system of definitions, one with a physicalist basis, might also be possible. Instead of ontological economy and a phenomenal basis, Carnap's project seems to have been the more Kantian one of indicating how semantic intersubjectivity is possible: How can it be that, even though I have only my own experiences and you have only yours, we can nevertheless share a common body of concepts? The answer is given in terms of shared inferential structure and identifying any given concept with a unique place within that shared overall structure. This is a highly holistic conception of concepts and it depends on thinking of the body of scientific commitments as a whole, as a unity.

The Aufbau was largely drafted before Carnap joined the Vienna Circle. Once there and under some influence from Neurath, Carnap campaigned more insistently for physicalism and for the unity of science. They seemed often to be two sides of the same coin. From 1933 onward there was a succession of monograph series with 'Unified Science' in the title. Until his death in 1945, Neurath was in each case the main editor and Carnap either the associate editor or one of the associate editors. The International Encyclopedia of Unified Science, begun in 1938 is undoubtedly the most famous of these. Carnap's own essay on this topic "Logical Foundations of the Unity of Science" (1938) was printed as part of the very first number in the encyclopedia.

The dates here are relevant because by the time of this essay Carnap had already decided (Carnap 1936-37) that theoretical terms could not in general be given explicit definitions in the observation language even though the observation reports were already in a physicalist vocabulary. The partially defined theoretical terms could not be eliminated. This seems to have caused Carnap no consternation at all, and it never seems to have occurred to him that there was any conflict whatever between this result and the unity of science. This is because by this point the elimination of concepts was not the point of the exercise; their inferential and evidential integration was.

In the 1936-37 article, "Testability and Meaning" Carnap called the partial definitions themselves "reduction sentences" and the system of definitions of theoretical terms, both partial and complete, as a reduction of the theoretical terms to the observational basis. Plainly he means by the word 'reduction' something other than what we currently mean, not that there is anything univocal about current uses of the word. By 'reduction' of vocabulary A to vocabulary B Carnap means the specification of the inferential relations that would allow us to say what sentences or combinations of sentences in A would count as evidence for sentences in B.

This is also the key to what Carnap means by the unity of the language of science. The language of science is unified, no matter how different and exotic its various technical vocabularies may be, when each of its terms is reduced to (can be tested in) a common public observation vocabulary. The call for the unity of the language of science, then, amounts to no more than the demand that the various claims of the separate sciences should be publicly testable in a common observation language. Controversies will of course arise as to what the observational vocabulary should be and what are the acceptable forms of linkage. Carnap's demand for unity in the language of science abstracts from those controversies to concentrate on the goal of public testability. That does not seem to be an unreasonable demand.

The unity of the language of science so far discussed is quite a different issue from the unity of the laws of science. And Carnap's attitudes toward them are quite different. The latter issue concerns the extent to which the laws of one special science can be inferred from those of another. Carnap tries to articulate what would be involved in such a unification, but he nowhere says that such a unity is either possible or mandatory. Finding any sort of inferential connections among sets of laws would be welcome of course. But the question of how much unity there is, if any, among the various sciences is an empirical question that philosophers are ill equipped to answer. Philosophers should not make pronouncements, especially in advance of having putative laws in hand, either that scientific laws are unified or that they are not. A certain modest deference to the empirical facts that philosophers generally do not have, again, does not seem unreasonable.

Taking unity as a working hypothesis, as some philosophers have done, amounts to looking for inferential and nomological connections among various sets of laws, but not to the assertion that such connection will be found. Even if we accept the idea that such connections would be welcome if found, the question of whether one should spend significant effort in looking for them is not thereby answered. That would be a difficult and delicate practical question of how to apportion one's research effort that for the purposes of this essay we must set aside.

There are two broad approaches to probability represented in logical empiricism. One of these, the so-called frequentist approach, has an extensive 19 th century history and was further developed from about 1920 onward by Richard von Mises and Hans Reichenbach. The other is the epistemic approach to probability. This goes back at least to Laplace at the end of the 18 th century. In the 20 th century Rudolf Carnap, who explored what he called logical probability, and Frank Ramsey and Richard Jeffrey whose accounts can be distinguished from Carnap's and are often called subjective probability, all defended the epistemic approach. While Ramsey visited the Vienna Circle he was not much influenced by its members on these matters. By contrast, Jeffrey studied and later collaborated with Carnap but also made significant contributions of his own.

It is natural to begin thinking about probabilities with a simple mathematical account that takes as its point of departure various games of chance involving cards, dice, or coins. Bettors have long noted that some outcomes are much more likely than others. In this context it is convenient to take the probability of a kind of outcome to be the ratio of such outcomes to all possible outcomes. Usually for reasons of symmetry in the physical set up, the possible outcomes are assumed to be equally likely. Where that assumption happens to be true or nearly so the empirical results of, say, a great many throws of a pair of dice tends to be close to what the simple mathematical account would suggest. Conversely, where the outcomes deviate from the expected ratios, bettors begin to suspect that the dice, coins, and cards (or the manipulations of them) are not all that they seem. The suspicion is that the outcomes are not equally likely and that the simple mathematical account does not apply.

These facts suggest both two limitations of the simple account and the beginnings of a way around them. The first limitation is that the account applies only where the outcomes can be partitioned into alternatives that are equally likely. This is not the case when dice are loaded or in such real world cases as radioactive decay or weather forecasting. A second limitation is that the account, in describing the possible outcomes as equally likely, implicitly appeals to the very probability notion for which clarification was sought. The realization that we can sometimes discover the falsehood of the assumption of equal likelihood and make a much more reasonable estimate of probability by making a large number of trials is very suggestive. And from his dissertation onward Reichenbach worked out a variety of imagined physical models that could guide ones thinking about probability in useful ways. The result is what is often called the frequency theory of probability (or sometimes the statistical frequency theory or the limit frequency theory).

Even a perfectly fair coin in an odd number of flips will never result in exactly the same number of heads and of tails. When the coin is fair and the number of flips is even, an outcome perfectly balanced between heads and tails is not guaranteed either. So, even on the assumption that the probability of the coin's coming up heads does not change over the course of the trials, we need to be cautious. A larger number of flips might make us more confident that the ratio we have seen is close to the "actual" value, but there is no finite number of flips after which we can say that the observed ratio is exactly right. We will never make an infinite number of flips either, and in actual cases a large finite number of flips might so erode the coin as to bias the coin and discredit the result. Notwithstanding these limitations on an actual series of trials one can imagine an infinite series of trials and define a notion of probability with respect to it. This raises its own difficulty, namely that ratios are not defined for infinite collections. They would be defined, however, for any finite initial segment of such an infinite series, thus giving a sequence of ratios. If this sequence of ratios settles down on a limit, the probability of the coin showing a head given that it has been flipped can be defined as the limit of the ratio of heads to total flips as the number of flips goes to infinity.

While probability thus defined has a somewhat counterfactual character, that is not an obvious defect. Moreover, this notion of probability applies perfectly well to biased coins and loaded dice, as well as to radioactive decay. On the surface at least it also seem to avoid using the notion of probability in its own definition, and in these respects it seems to be an important improvement over the simple mathematical model with which we began. The definition locates the probability objectively "out in nature" so to speak, and this comports well with Reichenbach's scientific realism.

A problem that remained troublesome concerns the fact that one often wants to assign probabilities to particular events, events that in the nature of things cannot be repeated in all their particularity. Thus it is unclear how a frequency theory of probability is to be applied to such individual cases. This is often called the problem of the single case. It is a little difficult to assess how serious this is, because in actual practice we often have no difficulty in making probability assignments to single cases. Suppose we are interested in the probability of rain tomorrow. Tomorrow will never be repeated, and we want to estimate the probability now. What we do is to look back through the records to find days relevantly like today and determine in what fraction of those cases those days were followed by rainy days and use that as our estimate. Even if we are comfortable with this practice, however, it is another matter to say why this should give us a reasonable estimate of the value of the limit involved in a logically impossible infinite sequence. This problem of the single case was much discussed, and Wesley Salmon made progress in dealing with it. Indeed, Salmon's account of statistical explanation can be viewed as a substantial mitigation of the problem of the single case (W. Salmon 1970).

There are residual difficulties in making estimates of the probabilities on the basis of finite evidence. The problem is that even when we are assured that the sequence of ratios has a limit, we have no a priori grounds for saying how close the current ratio is to that limit. We can boldly estimate the limit by means of the so-called "straight rule". This just takes the most recent ratio as the desired estimate. This is a good practical solution where the number of trials is already high, but this does not really say why the estimate should be good, how good it is supposed to be, or how many trials would be high enough. In addition, the straight rule can yield counterintuitive results where the number of trials is small.

Though there are these issues outstanding, frequency theories define a concept of probability indispensable for quantum theories and for a wide variety of other applications in the natural and social sciences. It was not the only concept of probability to be developed by the logical empiricist tradition. The primary other such concept was the epistemic conception of probability. We will begin with Carnap and then move to those who developed a subjectivist account.

Carnap is addressing a different issue than was addressed by von Mises and Reichenbach. Instead of focusing on physical phenomena and ratios within them, Carnap focuses on arguments and takes as his point of departure the widespread conviction that some arguments are stronger, in varying degrees, than others, even for the same conclusion. Similarly some bodies of evidence can give us more reason to believe a given conclusion than would another body of evidence. Carnap sets as his task the development of a quantitative concept of probability that will clarify and explicate these widespread convictions. Such a quantitative concept would be an extraordinarily useful tool, and it would be a useful successor to our ordinary, somewhat scattered notions of confirmation and induction.

Carnap approaches the problem by first considering extremely limited artificial languages and trying to find a confirmation function that will work for that. If he succeeds he would then try to develop an account that would work for a broader and richer range of languages. In this his approach is like that of a physicist developing a physical theory for the highly artificial situation of a billiard table or air track and then broadening the theory to deal with a wider range of cases. In Carnap's case, however, it is somewhat unclear what success would be in an artificial language very much unlike our own. In any case, Carnap is not trying to describe our linguistic habits but to clarify or even to replace them with something more useful.

As early as Logical Syntax (Carnap 1934/1937, 244/316-17) Carnap had suggested that Wittgenstein's remarks in the Tractatus about ranges ( Tractatus, 4.463) might be a starting point for thinking about probability. By 1945 Carnap also distinguished the two approaches described here, insisting that they were not competitors but were attempting to explicate two different concepts of probability. One need not choose one as the only concept; both concepts were useful. Reichenbach, by contrast, never conceded that both concepts were needed and insisted that his frequency notion could serve all epistemic purposes for which any notion of probability is needed.

Carnap's general strategy was first to identify a broad class of confirmation functions, as subjectivists Ramsay and de Finetti were also to do, and then find a natural way of limiting this class still further. The confirmation functions have to meet some basic mathematical conditions. The axioms that state these conditions partially define a function, and this function can be interpreted in a number of ways. Carnap himself lists three in Carnap 1950. In (1955), John Kemeny (one of Carnap's collaborators and later a co-inventor of BASIC programming language and still later president of Dartmouth College) gave an argument that persuaded Carnap that it was more fruitful to think of the function as indicating fair betting quotients rather than evidential support. This took Carnap even closer in conception to the work of such subjectivists as Ramsey and de Finetti. Indeed, the discussion of fair betting quotients, and related issues of Dutch book arguments had been initiated by de Finetti.

In Logical Foundations of Probability (1950) Carnap had discussed Bayes' theorem and promised to expand the discussion in a second volume. Carnap's interest in Baysianism grew, but that second volume never materialized, quite possibly because rapid development of the field was still under way at the time of Carnap's death. As his work proceeded Carnap tended to explain probabilities by reference to events and propositions rather than speak overtly about sentences. A similar change appears in the rest of Carnap's work as well. It is not clear, however, whether this amounts to a major change of view or a change in what he sees as the most felicitous mode of expression. As the years progressed Carnap tended to see the remaining differences between himself and his subjectivist co-workers as chiefly differences in emphasis. In any case the subjectivist tradition is now dominant in philosophical discussions of probability (Zabell 2007, 293). Richard Jeffrey whose own work arose out of logical empiricism carried on that tradition for 35 years after Carnap's death. Jeffrey himself made major contributions including a principle for updating ones beliefs when the evidence one learns is not certain. The world knows this principle as "Jeffrey conditionalization"; he called it simply "probability kinematics".

Popper's view of probability, his propensity theory, differs from either of the two approaches discussed above. Unlike the epistemic approach of Carnap and others, Popper was not trying to clarify inductive relations because he did not believe that there are inductive inferences. Theories can be corroborated by their passing severe tests, but they are not thereby inductively confirmed or made more probable. For a discussion of whether there are any significant similarities between Popper's idea of corroboration and the ideas of inductive confirmation that he rejects, see (Salmon 1967, 1968).

Propensities are thought of as tendencies of a physical event or state to produce another event or state. Because propensities are to be features of external events and not, to use Hume's phrase, relations of ideas, the propensity theory and the statistical-frequency theory are sometimes grouped together as accounts of chance. Popper has specifically applied propensities to single non-repeatable events (1957), and that suggests that the concept of propensity does not involve any essential reference to long sequences of events. Popper has also taken propensities as producing outcomes with a certain limit frequency (1959). This does suggest a rather closer tie to the statistical frequency approach. Later philosophers developed both sorts of propensity theories, single-case theories and long-run theories. (Gillies 2000) And like other approaches to probability and induction all these views remain controversial. While we will not discuss the relative merits of the various approaches further, those who are interested in Popper's views in this area should look at the many papers on probability, induction, confirmation, and corroboration, and Popper's replies, in The Philosophy of Karl Popper (Schilpp 1974).

In 1967 John Passmore reported that: "Logical positivism, then, is dead, or as dead as a philosophical movement ever becomes." (1967, 57) Earlier in the same article he had equated logical positivism with logical empiricism, so presumably that was dead too. At that time few would have disagreed with Passmore, even though Carnap was still alive and active. But in speaking of this movement Passmore was referring not to a movement but to specific doctrines, and his interpretation of them was much influenced by Ayer. Even so, Passmore conceded that the movement had left a legacy and that "the spirit which inspired the Vienna circle" persisted. It still does.

Part of the movement's legacy lies in contemporary philosophy of science. In the US nearly all philosophers of science can trace their academic lineages to Reichenbach. Most were either his students or students of his students and so on. His scientific realism inspired a generation of philosophers, even those clearly outside the movement. Even the reaction against various forms of realism that have appeared in recent decades have roots in the logical empiricist movement. Moreover, philosophers of science are expected to know a great deal of the science about which they philosophize and to be cautious in telling practicing scientists what concepts they may or may not use. In these respects and others contemporary philosophers promote a kind of naturalism, and by so doing they follow both the precept and the example of the logical empiricists.

There are other issues where the legacy of logical empiricism is still visible. Two different approaches to probability are still under discussion. One of them explores the objective chances of external events; this investigation follows in the tradition of the frequency theory of Reichenbach and von Mises. The second approach has an epistemic conception of probability as exemplified by Carnap. S.L. Zabell summarizes the current situation as follows:

But although the technical contributions of Carnap and his school remain of considerable interest today, Carnap's most lasting influence was more subtle but also more important: he largely shaped the way current philosophy views the nature and role of probability, in particular its widespread acceptance of the Bayesian paradigm (as, for example, in Earman, 1992; Howson and Urbach, 1993; and Jeffrey, 2004). (Zabell 2007, 294)

There is also a continuing concern for how the various sciences fit together. Some have scouted theoretical unification and others a more pluralistic model, just as the logical empiricists did. There was for a while a vogue for the disunity of science. Some even said that their conception of the disunity of science is just what Neurath meant by the unity of science. Parts of the discussion were intended as challenges to logical empiricism, but often the arguments used were pioneered by the logical empiricists themselves.

For the 30 years after Passmore's report metaphysics became ever more visible in philosophy. It was a diverse development, but in the self-conceptions of many of its most prominent practitioners there was no attempt to shun science or logic or to think that metaphysics had access to facts that were deeper than or beyond those that a proper science could reach. So the metaphysics that blossomed was not necessarily of the sort that Carnap and others combated. Most recently there are some in meta-ontology that want to reconsider and reconnect with Carnap's ontological caution.

Even in its heyday many philosophers who on either doctrinal or sociological grounds can be grouped with the logical empiricists did not see themselves that way. We should not expect philosophers today to identify with the movement either. Each generation finds its place by emphasizing its differences from what has gone before. But the spirit of the movement still has its adherents. There are many who value clarity and who want to understand the methodology of science, its structure, and its prospects. There are many who want to find a natural home within a broad conception of science for conceptual innovation, for logic and mathematics, and for their own study of methodology. And importantly there are those who see in science a prospect for intellectual and social reform and who see in their own study of science some hope for freeing us all from the merely habitual ways of thinking "by which we are now possessed" (Kuhn 1962, 1). These are the motives that define the movement called logical empiricism. As Twain might have said, the reports of its death are greatly exaggerated.

Cited Literature

Ayer, A.J., 1936, Language Truth, and Logic, London: Gollancz.

Carnap, R., 1928/1967, Der logische Aufbau der Welt, translated by R.A. George asThe Logical Structure of the World, Berkeley: University of California Press.

---, 1934/1937, Logische Syntax der Sprache, translated by A. Smeaton as The Logical Syntax of Language, London: Kegan Paul, Trench, Trubner & Co.

---, 1935, Philosophy and Logical Syntax, London: Kegan Paul, Trench, Trubner, & Co.

---, 1936-37, "Testability and Meaning", Philosophy of Science, 3: 419-71, 4: 1-40.

---, 1938, "Logical Foundations of the Unity of Science", International Encyclopedia of Unified Science (Volume 1, Number 1), Chicago: University of Chicago Press, 42-62.

---, 1942, Introduction to Semantics, Cambridge, MA: Harvard University Press.

---, 1950, Logical Foundations of Probability, Chicago: University of Chicago Press.

---, 1958 [2017], "Value Concepts", transcribed and translated by A. Carus, Synthese 194: 185-94. [Original manuscriptavailable online]

---, 1963a, "Carl G. Hempel on Scientific Theories", in The Philosophy of Rudolf Carnap, P.A. Schilpp (ed.), LaSalle, IL: Open Court, 958-66.

---, 1963b, "K.R. Popper on Probability and Induction", in The Philosophy of Rudolf Carnap, P.A. Schilpp (ed.), LaSalle, IL: Open Court, 995-998.

---, 1966, Philosophical Foundations of Physics, M. Gardner (ed.), New York: Basic Books.

Carus, A.W., 2007, Carnap and Twentieth-Century Thought, Cambridge: Cambridge University Press.

Creath, R., 1976, "On Kaplan on Carnap on Significance", Philosophical Studies, 30: 393-400.

---, 2009, "The Gentle Strength of Tolerance: The Logical Syntax of Language and Carnap's Philosophical Programme", inCarnap's Logical Syntax of Language, P. Wagner (ed.), Houndsmills, Basingstoke, UK: Palgrave Macmillan, 203-214.

Earman, J., 1992, Bayes or Bust: A Critical Examination of Bayesian Confirmation Theory, Cambridge, MA: MIT Press.

Friedman, M., 1987, "Carnap's Aufbau Reconsidered",Noûs, 21: 521-45.

Gillies, D., 2000, "Varieties of Propensity", British Journal for the Philosophy of Science, 51: 807-835.

Gödel, K., 1995, "Is Mathematics Syntax of Language?" in K. Gödel, Collected Works (Volume 3), S. Fefferman, et al. (eds.), Oxford: Oxford University Press, 334-362.

Hempel, C.G., 1950, "Problems and Changes in the Empiricist Criterion of Meaning", Revue International de Philosophie, 11: 41-63.

---, 1951, "The Concept of Cognitive Significance: A Reconsideration", Proceedings of the American Academy of Arts and Sciences, 80: 61-77.

Howson, C. and Urbach, P., 1993, Scientific Reasoning: The Bayesian Approach, LaSalle, IL: Open Court.

---, 2004, Subjective Probability: The Real Thing, Cambridge: Cambridge University Press.

Kaplan, D., 1975, "Significance and Analyticity: A Comment on Some Recent Proposals of Carnap", in Rudolf Carnap, Logical Empiricist, J. Hintikka (ed.), Dordrecht, Boston: Reidel, 87-94.

Kemeny, J., 1955, "Fair Bets and Inductive Probabilities", Journal of Symbolic Logic, 20: 263-73.

Kuhn, T., 1962, The Structure of Scientific Revolutions,International Encyclopedia of Unified Science (Volume II, Number 2), Chicago: University of Chicago Press.

Passmore, J., 1967, "Logical Positivism", The Encyclopedia of Philosophy (Volume 5), P. Edwards (ed.), New York: Macmillan, 52-57.

Popper, K., 1935/1959, Logik der Forschung, translated by the author asThe Logic of Scientific Discovery, New York: Basic Books.

---, 1957, "The Propensity Interpretation of the Calculus of Probability", S. Körner (ed.), The Colston Papers, 9: 65-70.

---, 1959, "The Propensity Interpretation of Probability", British Journal for the Philosophy of Science, 10: 25-42.

Quine, W.V., 1951, "Two Dogmas of Empiricism", Philosophical Review, 60: 20-43.

---, 1963, "Carnap and Logical Truth", in The Philosophy of Rudolf Carnap, P. Schilpp (ed.), LaSalle, IL: Open Court, 385-406.

---, 1974, The Roots of Reference, LaSalle, IL: Open Court.

Reichenbach, H., 1916/2008, Der Begriff der Wahrscheinlichkeit für die mathematische Darstellung der Wirklichkeit, edited and translated by F. Eberhardt and C. Glymour asThe Concept of Probability in the Mathematical Representation of Reality, LaSalle, IL: Open Court.

---, 1938, Experience and Prediction: An Analysis of the Foundations and the Structure of Knowledge, Chicago: University of Chicago Press.

Richardson, A., 1998, Carnap's Construction of the World: The Aufbau and the Emergence of Logical Empiricism, Cambridge: Cambridge University Press.

Russell, B., 1914, Our Knowledge of the External World as a Field for Scientific Method in Philosophy, LaSalle, IL: Open Court.

Salmon, W., 1967, The Foundations of Scientific Inference, Pittsburgh: University of Pittsburgh Press.

---, 1968, "The Justification of Inductive Rules of Inference", in The Problem of Inductive Logic, I. Lakatos (ed.), Amsterdam: North-Holland, 24-43.

---, 1970, ""Statistical Explanation", in Nature and Function of Scientific Theories, R. Colodny (ed.), Pittsburgh: University of Pittsburgh Press, 173-231.

Schilpp, P. (ed.), 1974, The Philosophy of Karl Popper, LaSalle, IL: Open Court.

Suppes, P., 1978, "The Plurality of Science", in PSA 1978: Proceedings of the 1978 Biennial Meeting of the Philosophy of Science Association (Volume 2), P. Asquith and I. Hacking (eds.), East Lansing, MI: Philosophy of Science Association, 3-16.

Tarski, A., 1936a/1956, "Der Wahrheitsbegriff in den formalisierten Sprachen", translated by J.H. Woodger as "The Concept of Truth in Formalized Languages" in Logic, Semantics, Metamathematics, by A. Tarski, Oxford: Clarendon Press, 152-278.

---, 1936b/1956, "Über den Begriff den logischen Folgerung", translated by J.H. Woodger as "On the Concept of Logical Consequence", in Logic, Semantics, Metamathematics, by A. Tarski, Oxford: Clarendon Press, 409-20.

Uebel, T., 2012, "Carnap, Philosophy, and 'Politics in its Broadest Sense'", in Carnap and the Legacy of Logical Empiricism, R. Creath (ed.), Vienna: Springer, 133-145.

---, 2013, "Logical Positivism - Logical Empiricism: What's in a Name?", Prespectives of Science, 21: 58-99.

Waismann, F., 1967/1979, Wittgenstein und der Wiener Kreis, translated by J. Schulte and B. McGinnis asWittgenstein and the Vienna Circle, Oxford: Basil Blackwell.

Wittgenstein, L., 1921/1922, Logische-Philosophische Abhandlung, translated by C.K. Ogden as Tractatus Logico-Philosophicus, London: Routledge & Kegan Paul.

Zabell, S. L., 2007, "Carnap on Probability and Induction", in The Cambridge Companion to Carnap, M. Friedman and R. Creath (eds.), Cambridge: Cambridge University Press, 273-294.

Selected Secondary Literature

Awodey, S. and A. W. Carus, 2004, "How Carnap Could Have Replied to Gödel", in S. Awodey and C. Klein (eds.), Carnap Brought Home: The View From Jena, LaSalle, IL: Open Court, 203-223.

Blatti, S. and S. Lapointe (eds.), 2016, Ontology After Carnap, Oxford: Oxford University Press.

Cartwright, N. , J. Cat, L. Fleck, and T. Übel, 1996, Otto Neurath: Philosophy Between Science and Politics, Cambridge: Cambridge University Press.

Carus, A.W., 2007, Carnap and Twentieth-Century Thought, Cambridge: Cambridge University Press.

Friedman, M., 1987, "Carnap's Aufbau Reconsidered",Noûs, 21: 521-45.

---, 1999, Reconsidering Logical Positivism, Cambridge: Cambridge University Press.

---, 2000, A Parting of the Ways: Carnap, Cassirer, and Heidegger, LaSalle, IL: Open Court.

Friedman, M. and R. Creath (eds.), 2007, The Cambridge Companion to Carnap, Cambridge: Cambridge University Press.

Frost-Arnold, G., 2013, Carnap, Tarski, and Quine at Harvard: Conversations of Logic, Mathematics, and Science, Chicago: Open Court.

Hintikka, J. (ed.), 1962, Logic and Language: Studies Dedicated to Professor Rudolf Carnap on the Occasion of His Seventieth Birthday, Dordrecht: Reidel.

--- (ed.), 1975, Rudolf Carnap, Logical Empiricist: Materials and Perspectives, Dordrecht: Reidel.

Howson, C., 1973, "Must the Logical Probability of Laws be Zero?" British Journal for Philosophy of Science, 24: 153-163.

Jeffrey, R., 1975, "Probability and Falsification: Critique of the Popper Program", Synthese, 30: 95-117.

---, 2004, Subjective Probability: The Real Thing, Cambridge: Cambridge University Press.

Mancosu, P., "Harvard 1940-41: Tarski, Carnap, and Quine on a Finitistic Language of Mathematics for Science", History and Philosophy of Logic, 26: 327-57.

Miller, D., 1997, "Sir Karl Raimund Popper, CH, FBA", Biographical Memoirs of Fellows of the Royal Society of London", 43: 367-409.

Parrini, P., W. Salmon, and M. Salmon (eds.), 2003, Logical Empiricism: Historical and Contemporary Perspectives, Pittsburgh: University of Pittsburgh Press.

Rescher, N. (ed.), 1985, The Heritage of Logical Positivism, Lanham, MD: University Presses of America.

Rescher, N., 2006, "The Berlin School of Logical Empiricism and Its Legacy, Erkenntnis, 64: 281-304.

Richardson, A., 1998, Carnap's Construction of the World: The Aufbauand the Emergence of Logical Empiricism, Cambridge: Cambridge University Press.

Richardson, A. and Übel, T. (eds.), 2007, The Cambridge Companion to Logical Empiricism, New York: Cambridge University Press.

Salmon, W. and G. Wolters (eds.), 1994, Language, Logic, and the Structure of Scientific Theories: The Carnap-Reichenbach Centennial, Pittsburgh: University of Pittsburgh Press, and Konstanz, Germany: University of Konstanz Press.

Sarkar, S., (ed.), 1992, Synthese: Carnap: A Centenary Reappraisal, Volume 93, Numbers 1-2.

Schilpp, P. (ed.), 1963, The Philosophy of Rudolf Carnap, LaSalle, IL: Open Court.

Spohn, W. (ed.), 1991, Erkenntnis: Special Volume in Honor of Rudolf Carnap and Hans Reichenbach, Volume 35, Numbers 1-3.

Stadler, F., 1997/2001, Studien zum Wiener Kreis: Entwicklung und Wirkung des Logischen Empiricismus im Kontext, translated by C. Nielsen, et al. asThe Vienna Circle: Studies in the Origins, Development and Influence of Logical Empiricism, Vienna: Springer.

Übel, T., 2007, Empiricism at the Crossroads: The Vienna Circle's Protocol-Sentence Debate Revisited, LaSalle, IL: Open Court.

Zabell, S. L., 1996, "Confirming Universal Generalizations", Erkenntnis, 45: 267-283.

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The term 'logical empiricism' has no very precise boundaries and still less that distinguishes it from 'logical positivism'. It is therefore hard to map.