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How does our experiences influence how we perceive others?

Our response and solutions to this question are below.

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This section contains our dialectical journals as well.

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Our Essential Question is directly related to Judge 5 in 12 Angry Men because the 5th Juror was defending the boy when the other judges began attacking the boy for living in the slums. He related his experiences to the boy by explaining that even he had lived in the slums, and them attacking people in the slums was untrue and that people can change. This relates to the essential question because it shows how Juror 5 used his past experience in the slums to tell the other jurors that they were being unfair. In addition, the 3rd Juror used his experiences with his elder kid to say that the boy must be bad, since in his experience, the kid ran away. Meanwhile, the 8th Juror explains how his experiences as a parent are very different from those of the 3rd Juror, and it makes him think that the kid is less guilty than the 3rd Juror is.

In addition, the boy has displayed behavior that he's learned over the years from his father, including violence and anger. This shows that the boy learned from his experiences at home that it is okay to display the same behavior to others, whether it is unconscious or conscious.

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- "light in this never-ending shade" - the shade represents the darkness in our world and the problems we face. The light represents how we can overcome those problems and fight for a better future.
- "braved the belly of the beast" - beast likely represents COVID, and this phrase represents the fact that we have overcome the worst of it, but we still have some left to go, and we must be brave and face it.

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Before Act II the current standing is 8 guilty 4 not guilty. Then juror 6 suggests taking another vote to check where each individual stands. This time they do the vote one by one. The vote is 6 to 6. After this the 10th juror makes an assumption about the boy calling him a kid like that, and implying he definitely is guilty because of how he perceives him.

“Six to six! I’m telling you, some of you people in here are out of your minds. A kid like that” (Rose 59).

In this quote the 10th juror is angry that 2 more people have voted not guilty. In the beginning it was 11 to 1 and more people have been slowly switching over. The 10th juror is adamant about him being guilty. He cannot view the situation from another perspective. He is only looking at the case for face value, and also using his perception of the boy as a bias towards his vote. This makes him call the others “out of their minds” as he cannot fathom how someone can think differently. He also calls the kid a “kid like that” implying he has a bias.

This quote connects to the essential question because it is about the 10th juror's perception of the boy based on his experience and attitude. The 10th juror has been angry the whole time, and has been wanting to get it over with from the get go. This attitude makes his experience a foul one. This experience makes him angry, and makes him jump to conclusions quickly. This all makes him very biased towards his own perspective. When you have this attitude it gives you a negative experience making you biased and self-centered.

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Our experiences will give us different backgrounds which can relate to others and make us judge them in a certain way.

Examples:
- People who wrote the constitution never were slaves
- The people invading ukraine have never lived there, and people of different races never experience what the other has

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The alliteration in the stanza like "fierce and free", "benevolent but bold", and "inaction and inertia", bring a very powerful tone of obligation in the stanza. It makes people feel like they have to take action and bring change in society.

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Logos: The beginning of Paragraph 2 explains how a black girl now has a lot more opportunities than before, as a free person rather than a slave, showing improvement in our society since our nation's founding. However, it also explains how she can dream to become a president but isn't there yet, which shows how we still have a way to go in this regard. In addition, Paragraph 7 explains how democracy can be attacked but never defeated. This shows how in the end, the people will be equal and we can reach this goal.

Ethos: Gorman makes people trust her by proving that she is being greatly affected by this issue, in paragraph 2. She also keeps saying "we", saying that we are all in this together, including her, so she can talk about it.

Pathos: Gorman uses very powerful words and phrases in order to make people reading/listening feel pride for the nation, but also understand the improvements we can make. For example, "we grieved, we grew, even as we hurt, we hoped" makes the audience feel hopeful, making people listen more to Gorman for inspiration.

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The diction in Stanza 7 can be used to contribute to 2 main ideas: fear and hope.
- Fear: Using words like "catastrophe", "terrifying", and "feared in its inception" make people feel some fear for what the future holds
- Hope: Using phrases like "we trust", "redemption", "laughter to ourselves", and "how could catastrophe possibly prevail over us", Gorman makes us feel like we can overcome the problems that can destroy our future.

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Connection: Muslims and Hindus never saw life from the other's perspective. Therefore, neither can see why the other is fighting and try to have peace.

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Connection: This is an example of ethnic cleansing, which is where a group exterminates all of a certain ethnicity because they believe that group is inferior. This perspective on people of that ethnicity is shaped by people's experiences with them or by the lack of them.

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In August 2017, a deadly crackdown by Myanmar's army on Rohingya Muslims sent hundreds of thousands fleeing across the border into Bangladesh.

They risked everything to escape by sea or on foot a military offensive which the United Nations later described as a "textbook example of ethnic cleansing".

In January 2020, the UN's top court ordered the Buddhist-majority country to take measures to protect members of its Rohingya community from genocide.

But the army in Myanmar (formerly Burma) has said it was fighting Rohingya militants and denies targeting civilians. The country's leader Aung San Suu Kyi, once a human rights icon, has repeatedly denied allegations of genocide.

Who are the Rohingya?

Described by UN Secretary-General Antonio Guterres as "one of, if not the, most discriminated people in the world", the Rohingya are one of Myanmar's many ethnic minorities.

The Rohingya, who numbered around one million in Myanmar at the start of 2017, are one of the many ethnic minorities in the country. Rohingya Muslims represent the largest percentage of Muslims in Myanmar, with the majority living in Rakhine state.

They have their own language and culture and say they are descendants of Arab traders and other groups who have been in the region for generations.

But the government of Myanmar, a predominantly Buddhist country, denies the Rohingya citizenship and even excluded them from the 2014 census, refusing to recognise them as a people.

It sees them as illegal immigrants from Bangladesh.

Since the 1970s, Rohingya have migrated across the region in significant numbers. Estimates of their numbers are often much higher than official figures.

In the last few years, before the latest crisis, thousands of Rohingya made perilous journeys out of Myanmar to escape communal violence or alleged abuses by the security forces.

The exodus began on 25 August 2017 after Rohingya Arsa militants launched deadly attacks on more than 30 police posts.

Rohingyas arriving in Bangladesh said they fled after troops, backed by local Buddhist mobs, responded by burning their villages and attacking and killing civilians.

At least 6,700 Rohingya, including at least 730 children under the age of five, were killed in the month after the violence broke out, according to medical charity Médecins Sans Frontières (MSF).

Amnesty International says the Myanmar military also raped and abused Rohingya women and girls.

The government, which puts the number of dead at 400, claims that "clearance operations" against the militants ended on 5 September, but BBC correspondents have seen evidence that they continued after that date.

At least 288 villages were partially or totally destroyed by fire in northern Rakhine state after August 2017, according to analysis of satellite imagery by Human Rights Watch.

The imagery shows many areas where Rohingya villages were reduced to smouldering rubble, while nearby ethnic Rakhine villages were left intact.

Human Rights Watch say most damage occurred in Maungdaw Township, between 25 August and 25 September 2017 - with many villages destroyed after 5 September, when Myanmar's de facto leader, Aung San Suu Kyi, said security force operations had ended.

A report published by UN investigators in August 2018 accused Myanmar's military of carrying out mass killings and rapes with "genocidal intent".

The ICJ case, lodged by the small Muslim-majority nation of The Gambia, in West Africa, on behalf of dozens of other Muslim countries, called for emergency measures to be taken against the Myanmar military, known as Tatmadaw, until a fuller investigation could be launched.

Aung San Suu Kyi rejected allegations of genocide when she appeared at the court in December 2019.

But in January 2020, the court's initial ruling ordered Myanmar to take emergency measures to protect the Rohingya from being persecuted and killed.

While the ICJ only rules on disputes between states, the International Criminal Court (ICC) has the authority to try individuals accused of war crimes or crimes against humanity. The body approved a full investigation into the case of the Rohingya in Myanmar in November.

Although Myanmar itself is not a member of the court, the ICC ruled it had jurisdiction in the case because Bangladesh, where victims fled to, is a member.

Myanmar has long denied carrying out genocide and says it is carrying out its own investigations into the events of 2017. The country's Independent Commission of Enquiry (ICOE) admitted that members of the security forces may have carried out "war crimes, serious human rights violations, and violations of domestic law", but claimed there was no evidence of genocide.

Its full report has not yet been released, but questions have been raised.

With more than half a million Rohingya believed to still be living in Myanmar's northern Rakhine province, UN investigators have warned there is a "serious risk that genocidal actions may occur or recur".

The situation that led to "killings, rapes and gang rapes, torture, forced displacement and other grave rights violations" in 2017 remained unchanged, the investigators said in September, blaming a lack of accountability and Myanmar's failure to fully investigate allegations or criminalise genocide.

Rakhine province itself is the site of an ongoing conflict between the army and rebels from the Buddhist-majority Rakhine ethnic group.

What about the refugees?

The massive numbers of refugees who fled to Bangladesh in 2017 joined hundreds of thousands of Rohingya who had fled Myanmar in previous years.

Kutupalong, the largest refugee settlement in the world according to UNHCR, is home to more than 600,000 refugees alone.

While an agreement for the return of refugees was reached in early 2018, none returned. They said they would not consider going back to Myanmar unless they were given guarantees they would be given citizenship.

And as a BBC investigation showed, even those considering returning in the future may not be able to, with villages destroyed to make way for government facilities.

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Myanmar Rohingya: What you need to know about the crisis

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Who are they, why are they fleeing from Myanmar and what is the international community doing?

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Each of the images here show another part of America that Gorman describes. For example, the sun baked south is shown through a sun.

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Connection: This is a symbol of the Cold War between the US and USSR. This conflict was shaped and defined by the conflict of capitalism and democracy vs. communism. This conflict emerged because poor people believed in communism while the rich believed in capitalism, which divided people.

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1. Now that we finished act 1, I have a pretty good understanding of what's happening in the play.
2. I'm able to follow the plot when reading in class.
3. I think having different students read as each of the jurors helps me get a stronger understanding of the play since it helps me follow along better. The discussions after reading and activities we've done has also been helpful to me.

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1. So far I think I have a good understanding of Act 1, but sometimes I forget what is judge is what and what they are trying to say. But the movie helps with this.
2. I am able to follow well when we read during class. But I occasionally forget which judge is which.
3. I think something that has been helpful to me us that when I'm reading during class on a character it helps me understand them better and also watching the movie.

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1. I feel like I understand most of Act I, and can understand the characters and how each of them are feeling at the moment. Of course, there are still many more things that can be uncovered through deeper analysis, but I feel like I understand the characters' basic motives and ideas.

2. I am able to follow along pretty well. Being able to read the play on my own computer while reading as a class really helps with this, and acting it out makes all of the emotions more prevalent and easy-to-understand.

3. All of the discussions seem to be helping with understanding the play better, with the campfires and other forms of more individual discussion. Hearing other people's thoughts, connections, and analysis of the play gives me a new perspective and lets me understand the play from all angles. However, I feel like most of the activities we do as individuals are not as helpful, since I mainly understand what I do in these assignments while reading the play as a class.

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1. I think the plot is progressing heavily and some major points are starting to be made, but I still have been able to keep up with everything
2. When we read it is fairly easy to keep up, but some parts are harder to digest.
3. The movie has been helping me a lot with the plot and the tones of the people as they talk. The campfires are ok, but I don't find them as important as watching the movie.

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1. I am understanding the play well.
2. I can follow the plot well when we read during class
3. Having people read and play out the part of each juror is helpful because it helps in getting specific lines stuck in my brain which helps me in understanding the plot

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"And yet the dawn is ours before we knew it, somehow we've weathered and witnessed a nation that isn't broken but simply unfinished." I chose this one because we still are growing as a nation.
"We, the successors of a country and a time where a skinny black girl descended from slaves and raised by a single mother can dream of becoming a president only to find herself reciting for one." This shows improvement in the history of America that a black women can now dream to be in the strongest position of the country, and we still have more to improve on.

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"We will not march back to what was but move to what shall be, a country that is bruised but whole, benevolent but bold, fierce and free, we will not be turned around or interrupted by intimidation because we know our inaction and inertia will be the inheritance of the next generation, our blunders become their burden. But one thing is certain: if we merge mercy with might and might with right, then love becomes our legacy and change our children's birthright."

Caption: I chose this quote (Paragraph 8) because there are many strong and impactful words and phrases in this quote. It explains how we need to make a change, or else the burden of that just moves on to the next person. Inertia especially explains how if we do something, the future generations will continue, while if we don't, the future is going to need to face the same decision, and it will be hard to ever start.

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"the new dawn blooms as we free it, for there is always light if only we're brave enough to see it, if only we're brave enough to be it."
i chose these lines because it says that if we don't go out of our comfort zones how will be grow

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“and the norms and notions
of what just is
isn't always just-ice.”
I chose this because I feel like sometimes we as a society overlook certain things that are harmful just because they happen often or “just is”

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I learned that Juror 6 is very insecure and doesn't have very strong opinions. He is very reserved and doesn't speak up at all and when he does he is very nervous and reserved.

I feel like this way is much more efficient and much easier, as you don't wait as long for people to speak, you can tell who wants to speak, and you can have a much faster paced and more in depth discussion for the topic.

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I learned that Juror 3 is very talkative and self centered. He doesn't have interest in listening to other opinion and is very firm believer that his opinion is the only correct one.
I enjoy this discussion setting better than the campfire since i feel more comfortable to speak in smaller groups.

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1. I learned that juror number 10 might have a sick appearance because he has a cold in the summer time when it is not common.
2. I liked the campfire better because we have a chance to hear what more people have to say, rather than just in the group.

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1. What did you learn about another character that stands out to you?
I learned a lot about the 10th Juror. It's very interesting that the things that the 10th Juror does fit an old-man character, and that the 10th Juror just seems like one of the bad guys of the play.

2. How do you feel you did in this discussion setting as opposed to the campfire?
I felt similar to the campfire, since I participated about the same amount in both settings.

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1. I think one thing that stood out to me was that juror number 6 doesn't talk to much and has very few lines, I didn't realize that before.
2. I think it was better that the campfire, since there were less people per group so I think it was easier to discuss

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1. I learned that Juror 3 has a son who he does not have an amicable relationship with. This sheds some light on why he wants the boy to be proven guilty because maybe the boy reminds him of his son.

2. I feel like I did better in this discussion setting because there are less people you are speaking to which allows me to be able to speak more.
-Rayan

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Connection: Because of the wars/conflicts that have already occurred between Sunnis and Shias, many Muslims believe that the other group is very wrong, and that people of the other group are bad people.

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Connection: Women who went through the process of abortion will likely hold an opinion on the subject, and may feel offended by/disagree with anyone else who holds the opposing opinion.

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Connection: This shows a time when the US, Britain, and Nazi Germany were trying to reach an agreement over Hitler's aggressive acts. During this, Hitler lied about not invading any more territory, and because the US and Britain experienced this lying, they did not like Germans and went to war.

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Connection: This was a meeting between the US President and Soviet leader to discuss the end of the Cold War. The end of the war came about when Gorbachev (the Soviet leader) came to power and began instituting capitalist reforms because he experienced a worse Soviet Union due to communism.

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Connection: The way that people act is defined by their experiences. Someone who has been surrounded by people of some personality may also become that personality.

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Connection: The country of Pakistan was formed by Muslims who felt that they were a minority in India. They had experiences with being underrepresented in a majority-Hindu country, which led them to create their own state.

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This movement was Indians rising up against the British. It was caused by the Indians experiencing injustices with the British system, such as monopolies on trade.

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Connection: This is a website that explains about the Great Schism. People who experienced good things with the Catholic Church stayed with Catholicism, while people who saw bad things with the church became Protestant, which caused a divide in Christianity.

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On July 16, 1054, Patriarch of Constantinople Michael Cerularius was excommunicated, starting the “Great Schism” that created the two largest denominations in Christianity—the Roman Catholic and Eastern Orthodox faiths.

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Connection: This was a part of the movement of Indians against the British, where Indians who had experienced oppression had begun to fight back (nonviolently) against the British. This shows that Indians' experiences led them to try to protest against another group, the British.

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Connection: This is also related to the partition of India. Hindus and Indians disagree on the subject of whether India should be split because they have experienced different things.

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Connection: This image shows the British taking over India. The British took over India because they believed that they were superior, while Indians wanted their independence because they had no such belief, and didn't want to be controlled by foreigners.

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Connection: Amanda Gorman's poem "The Hill We Climb" is related to the essential question because it talks a lot about how our different backgrounds (aka experiences) give us unique perspectives but also biases, and that we should try to work together to resolve these biases.

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Connection: Bias is caused by our different experiences. This is because when we see a new person who is similar to a different person that we already know, we tend to relate them and assume that the new person is similar to the person we used to know. This means that if we didn't like the person we already knew, we tend to not like the new person either.

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Connection: This podcast discusses biases and the importance of avoiding them. Biases are caused by our different experiences, which is discussed in the post directly above this.

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‎The Cognitive Bias Podcast on Apple Podcasts

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Connection: This post is referring to the discrimination against Jews that has occurred throughout history. Many people have experienced others' perspectives of anti-Semitism, and so they adopt the same ideas. This makes people not like Jews, and continuously spreads this idea.

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Connection: This image shows slavery. Slaves experience brutality from others, which makes them not like the people who are controlling them. Non-slaves see slaves as primitive creatures or inferior, which makes them not see slaves as humans or people who are worth anything.

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Connection: This refers to the conflict between Palestine and Israel. This is driven by Jews having experienced discrimination and wanting a safe home, which they found in Israel. Meanwhile, Palestinians used to have a unified state and experienced an influx of Jews, which made them dislike Jews and want to be re-unified with Israel.

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Connection: This article discusses implicit bias in healthcare. This implicit bias is mainly caused by a person having experiences with a group of people OR having experiences with someone who also has a bias. This bias causes us to treat different people different ways.

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Abstract

Background

Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients.

Methods

PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies.

Results

Forty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals' attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care.

Discussion

The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics.

Conclusions

Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.

Keywords: Implicit bias, Prejudice, Stereotyping, Attitudes of health personnel, Healthcare disparities

Background

A patient should not expect to receive a lower standard of care because of her race, age or any other irrelevant characteristic. However, implicit associations (unconscious, uncontrollable, or arational processes) may influence our judgements resulting in bias. Implicit biases occur between a group or category attribute, such as being black, and a negative evaluation (implicit prejudice) or another category attribute, such as being violent (implicit stereotype) [ 1].1 In addition to affecting judgements, implicit biases manifest in our non-verbal behaviour towards others, such as frequency of eye contact and physical proximity. Implicit biases explain a potential dissociation between what a person explicitly believes and wants to do (e.g. treat everyone equally) and the hidden influence of negative implicit associations on her thoughts and action (e.g. perceiving a black patient as less competent and thus deciding not to prescribe the patient a medication).

The term 'bias' is typically used to refer to both implicit stereotypes and prejudices and raises serious concerns in healthcare. Psychologists often define bias broadly; such as 'the negative evaluation of one group and its members relative to another' [ 2]. Another way to define bias is to stipulate that an implicit association represents a bias only when likely to have a negative impact on an already disadvantaged group; e.g. if someone associates young girls with dolls, this would count as a bias. It is not itself a negative evaluation, but it supports an image of femininity that may prevent girls from excelling in areas traditionally considered 'masculine' such as mathematics [ 3]. Another option is to stipulate that biases are not inherently bad, but only to be avoided when they incline us away from the truth [ 4].

In healthcare, we need to think carefully about exactly what is meant by bias. To fulfil the goal of delivering impartial care, healthcare professionals should be wary of any kind of negative evaluation they make that is linked to membership of a group or to a particular characteristic. The psychologists' definition of bias thus may be adequate for the case of implicit prejudice; there are unlikely, in the context of healthcare, to be any justified reasons for negative evaluations related to group membership. The case of implicit stereotypes differs slightly because stereotypes can be damaging even when they are not negative per se. At least at a theoretical level, there is a difference between an implicit stereotype that leads to a distorted judgement and a legitimate association that correctly tracks real world statistical information. Here, the other definitions of bias presented above may prove more useful.

The majority of people tested from all over the world and within a wide range of demographics show responses to the most widely used test of implicit attitudes, the Implicit Association Test (IAT), that indicate a level of implicit anti-black bias [ 5]. Other biases tested include gender, ethnicity, nationality and sexual orientation; there is evidence that these implicit attitudes are widespread among the population worldwide and influence behaviour outside the laboratory [ 6, 7]. For instance, one widely cited study found that simply changing names from white-sounding ones to black-sounding ones on CVs in the US had a negative effect on callbacks [ 8]. Implicit bias was suspected to be the culprit, and a replication of the study in Sweden, using Arab-sounding names instead of Swedish-sounding names, did in fact find a correlation between the HR professionals who preferred the CVs with Swedish-sounding names and a higher level of implicit bias towards Arabs [ 9].

We may consciously reject negative images and ideas associated with disadvantaged groups (and may belong to these groups ourselves), but we have all been immersed in cultures where these groups are constantly depicted in stereotyped and pejorative ways. Hence the description of 'aversive racists': those who explicitly reject racist ideas, but who are found to have implicit race bias when they take a race IAT [ 10]. Although there is currently a lack of understanding of the exact mechanism by which cultural immersion translates into implicit stereotypes and prejudices, the widespread presence of these biases in egalitarian-minded individuals suggests that culture has more influence than many previously thought.

The implicit biases of concern to health care professionals are those that operate to the disadvantage of those who are already vulnerable. Examples include minority ethnic populations, immigrants, the poor, low health-literacy individuals, sexual minorities, children, women, the elderly, the mentally ill, the overweight and the disabled, but anyone may be rendered vulnerable given a certain context [ 11]. The vulnerable in health-care are typically members of groups who are already disadvantaged on many levels. Work in political philosophy, such as the De-Shalit and Wolff concept of 'corrosive disadvantage', a disadvantage that is likely to lead to further disadvantages, is relevant here [ 12]. For instance, if a person is poor and constantly worried about making ends meet, this is a disadvantage in itself, but can be corrosive when it leads to further disadvantages. In a country such as Switzerland, where private health insurance is mandatory and yearly premiums can be lowered by increasing the deductible, a high deductible may lead such a person to refrain from visiting a physician because of the potential cost incurred. This, in turn, could mean that the diagnosis of a serious illness is delayed leading to poorer health. In this case, being poor is a corrosive disadvantage because it leads to a further disadvantage of poor health.

The presence of implicit biases among healthcare professionals and the effect on quality of clinical care is a cause for concern [ 13- 15]. In the US, racial healthcare disparities are widely documented and implicit race bias is one possible cause. Two excellent literature reviews on the issue of implicit bias in healthcare have recently been published [ 16, 17]. One is a narrative review that selects the most significant recent studies to provide a helpful overall picture of the current state of the research in healthcare on implicit bias [ 16]. The other is a systematic review that focusses solely on racial bias and thus captures only studies conducted in the US, where race is the most prominent issue [ 17]. Our review differs from the first because it poses a specific question, is systematic in its collection of studies, and includes an examination of studies solely employing the vignette method. Its systematic method lends weight to the evidence it provides and its inclusion of the vignette method enables it to compare two different literatures on bias in healthcare. It differs from the second because it includes all types of bias, not only racial; partly as a consequence, it captures many studies conducted outside the US. It is important to include studies conducted in non-US countries because race understood as white/black is not the source of the most potentially harmful stereotypes and disparities in all cultural contexts. For example, a recent vignette study in Switzerland found that in the German-speaking part of the country, physicians displayed negative bias in treatment decisions towards fictional Serbian patients (skin colour was unspecified, but it would typically be assumed to be white), but no significant negative bias towards fictional patients from Ghana (skin colour would be assumed to be black) [ 18]. In the Swiss German context, the issue of skin colour may thus be less significant for potential bias than that of country of origin.2

Methods

Data sources and search strategy

Our research question was: do trained healthcare professionals display implicit biases towards certain types of patient? PubMed (Medline), PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. When we performed exploratory searches on PubMed before conducting the final search, we noticed that in 2003 there was a sharp increase in the number of articles on implicit bias and so we decided to begin from this year. The final searches were conducted on the 31st March 2013. We used a combination of subject headings and free text terms that related to the attitudes of healthcare professionals (e.g. "physician-patient relations", "attitude of health personnel"), implicit biases (e.g. "prejudice", "stereotyping", "unconscious bias"), particular kinds of discrimination (e.g. "aversive racism", anti-fat bias", "women's health"), and healthcare disparities (e.g. "health status disparities", "delivery of health care") which were combined with the Boolean operators "AND" and "OR".

Study selection

3767 titles were retrieved and independently screened by the two reviewers (SH and CF). The titles that were agreed by both after discussion to be ineligible according to our inclusion criteria were discarded (3498) and the abstracts of the remaining articles (269) were independently screened by both reviewers. Abstracts that were agreed by both reviewers to be ineligible according to our inclusion criteria were discarded (241). When the ineligible abstracts were discarded, the remaining 28 articles were read and independently rated by us both. Out of these, 27 articles were agreed after discussion to merit inclusion in the final selection. One article was excluded at this stage because it did not fit our inclusion criteria (it did not employ the assumption method or an implicit measure). Additionally, the reference lists of these 27 articles were manually scanned by CF, and the full text articles resulting from this were independently read by both reviewers, resulting in the inclusion of a further 11 articles that both reviewers agreed fitted the inclusion criteria. After a repeat process of scanning the reference lists of the 11 articles from the second round, the final number of eligible articles was 42. All disagreements were resolved through discussion.

The inclusion criteria were:

1. A method identifying implicit rather than explicit biases.

2. Participants were physicians or nurses who had completed their studies.

3. Written in English or another language spoken by CF or SH (CF: French, Italian, Spanish, Catalan; SH: French, Italian, German).

There is no clear consensus on the meaning of the term 'implicit'. The term is used in psychology to refer to a feature or features of a mental process. We chose a wide negative definition of implicit processes, assuming that implicit social cognition is involved in the absence of any of the four features that characterise explicit cognition: intention, conscious availability, controllability, and the need for mental resources. This absence does not rule out the involvement of explicit processes, but indicates the presence of implicit processes. While most institutional policies against bias focus on explicit cognition, research on implicit bias shows that this is mistaken [ 6].

There is broad agreement in psychology that methods known as 'implicit measures', including the affective priming task, the IAT and the affective Simon task, reveal implicit attitudes [ 19]. We included articles using these measures. We also included studies that employed a method popular in bioethics literature that we label 'the assumption method'. It involves measuring differences across participants in response to clinical vignettes, identical except for one feature, such as the race, of the character in the vignette. There is no direct measure of the implicitness or non-explicitness of the processes at work in participants; instead, there is an assumption that the majority are explicitly motivated to disregard factors such as race. If there is a statistically significant difference in the diagnosis or treatment prescribed correlated with -for example- the race of the patient, the researchers infer that it is partly a result of implicit processes in the physicians' decision-making. The assumption method of measuring implicit bias has been used in a variety of naturalistic contexts where it is harder to bring subjects into the laboratory. It is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias, if not as an implicit measure in itself [ 6].

Studies that used self-report questionnaires were not included because, although they can use subtle methods to estimate a subject's attitudes, they are typically used in psychology as a measure of explicit mental processes. There are potential problems with the implicit/explicit distinction as applied to psychological measures and it may be preferable in future research to speak of 'direct' and 'indirect' measures, but for the purposes of the review we followed this convention in psychology. The original idea behind implicit measures was that they attempted to measure something other than explicit mental processes, whereas self-report questionnaires ask a subject direct questions and thus prompt a chain of explicit conscious reasoning in the subject.

Data extraction

Data were extracted by CF and reviewed by SH for accuracy and completeness. All disagreements with the information extracted were resolved through discussion. We contacted the corresponding author of an article to obtain information that was not available in the published manuscript that related to the nature of the presentation given to recruit participants, but received no response.

Results

Identified studies

The eligible studies are described in Table 1 and their main characteristics are outlined in Table 2 . The most frequently examined biases were racial/ethnic and gender, but ten other biases were investigated (Table 2 ). Four of the assumption studies compared results from two or more countries to explore effects of differences in healthcare systems.

Table 1

Year

First author

Country

Method

Population

Recruitment

Response rate

Main findings (relevant to systematic review)

Age

AIDS patients

Brain injured patients who have contributed to their injury

Disability

Gender

Intravenous Drug Users (IDUs)

Mentally ill

Multiple biases

Racial/ethnic

2013a

Blair [ 44]

US

IAT (prejudice) and interpersonal interaction measures

134 clinicians

Data for clinicians collected in the Blair [ 44] study. Primary data from patients in a broader study on hypertension.

60%

Clinicians with greater implicit bias against blacks were rated lower in patient-centred care by their black patients as compared with a reference group of white patients.

Weight

Table 2

Studies (N = 42)

Method

Assumption method

25 [ 25- 41, 43, 58, 59, 61, 63- 66]

(of which: IAT combined with behaviour or decision)

9 [ 23, 24, 42, 44- 48, 67]

Setting and type of test

IAT - implicit stereotype

5 [ 23, 45- 47, 50]

IAT - standard

13 [ 22- 24, 42, 44- 47, 50, 60, 62, 67, 68]

(of which: photos in addition)

1 [ 43]

Assumption method - controlled setting

16 [ 27- 39, 41, 58, 63]

Assumption method - uncontrolled setting

8 [ 25, 26, 40, 43, 61, 64- 66]

Bias(es) studied

Racial/ethnic

27 [ 20- 24, 27- 41, 43- 47, 67]

Gender

14 [ 27- 38, 63, 66]

Mental illness

4 [ 26, 42, 64, 65]

Country of study

US

27 [ 20- 24, 27- 41, 43- 47, 62, 66]

UK

8 [ 26- 29, 31, 32, 58, 59]

Participants ( N  = 15148)

Profession of participants

Physicians

12156

Nurses

740

Either physicians or nurses

1404

'Clinicians', or 'mental health professionals' (at least some of whom were nurses and physicians)

834

Psychologists

12

Medical Students

2

The 14 assumption method studies examining multiple biases investigated interactions between biases. They recorded the socio-demographic characteristics of the participants to reveal complex interactions between physician characteristics and the characteristics of the imaginary 'patient' in the vignette.

All IAT studies measured implicit prejudice; five also measured implicit stereotypes. When implicit prejudice is measured, words or images from one category are matched with positive or negative words (e.g., black faces with 'pleasant'). When implicit stereotypes are measured, words or images from one category are matched with words from a conceptual category (e.g. female faces and 'home').

Nine IAT studies combined the IAT with a measure of physician behaviour or treatment decision to see if there were correlations between these and levels of implicit bias.

The subliminal priming studies were dissimilar: one was an exploratory study to see if certain diseases were stereotypically associated with African Americans, using faces as primes and reaction times to the names of diseases as the measure of implicit association; the other study used race words as primes and tested the effect of time pressure on responses to a clinical vignette.

A variety of media were used for the clinical vignette and the method of questioning participants within the assumption method. One unusual study used simulations of actual encounters with patients, hiring actors and using a set for the physicians to role-play. Physicians' treatment decisions were recorded by observers, and the physician recorded his own diagnosis, prognosis and perceptions after the encounter.

Limitations

Of specific studies

Limitations are detailed in Table 3 . Some studies failed to report response rates, or to provide full information on statistical methods or participant characteristics. Some had very small sample sizes and the majority did not mention calculating the power of their sample. Some authors explicitly informed participants of the purpose of the study, or gave participants questionnaires or other tests that indicated the subject of the study before presenting them with the vignette. For optimal results, participants should not be alerted to the particular patient characteristic(s) under study, particularly in an assumption study where knowing the characteristic(s) may influence the interpretation of the vignette. In IAT studies, this is less worrying because IAT effects are to some extent uncontrollable.

Of the field

Implicit bias in healthcare is an emerging field of research with no established methodology. This is to be expected and is not a problem in itself, but it does present an obstacle when conducting a review of this kind. The range of methods used and the variety of journals with differing standards and protocols for describing experiments made it difficult to compare the results. In addition, authors focusing on a particular bias (e.g. gender), often in combination with a particular health issue (e.g. heart disease), frequently did not appear to be familiar with one another's research. This lack of familiarity meant that often used different terms to describe the same phenomenon, which also made conducting the review more difficult.

Few of the existing results can be described as 'real world' treatment outcomes. The two priming studies involved very small samples and were more exploratory than result-seeking [ 20, 21]. The IAT and assumption studies were conducted under laboratory conditions. The only three studies conducted in naturalistic settings combined the IAT with measures of physician-patient interaction [ 22- 24]. However, many of the assumption studies attempted to make their vignettes as realistic as possible by having them validated by clinicians [ 25- 41] and also by having participants view/read the vignettes as part of a normal day at work [ 27- 36, 39, 41].

Because the studies of interest used psychological techniques, but were mainly to be found in a medical database (PubMed), the classification of the studies was not always optimal. There is no heading in Medline for 'implicit bias' and studies using similar methods were sometimes categorized under different subject headings, some of which were introduced during the last ten years, which increased the risk of missing eligible studies.

Existence of implicit biases/stereotypes in healthcare professionals and influence on quality of care

Healthcare professionals have implicit biases

Almost all studies found evidence for implicit biases among physicians and nurses. Based on the available evidence, physicians and nurses manifest implicit biases to a similar degree as the general population. The following characteristics are at issue: race/ethnicity, gender, socio-economic status (SES), age, mental illness, weight, having AIDS, brain injured patients perceived to have contributed to their injury,3 intravenous drug users, disability, and social circumstances.

Of the seven studies that did not find evidence of bias, one compared the mentally ill with another potentially unfavourable category, welfare recipients; this study did find a positive correlation between levels of implicit bias and over-diagnosis of the mentally ill patient in the vignette [ 42]. Another used simulated interactions with actors, which may result in participants being on 'best behaviour' in the role-play [ 41]. The two studies that reported no evidence of bias in diagnosis of depression found that physicians' estimates of SES were influenced by race (lower SES estimated for black patients); [ 37, 38] one reported that estimates of SES in turn were significantly related to estimates of patient demeanour (lower SES associated with hostile patient demeanour) [ 37]. A further study failed to find differences due to patient race in the prescription of opioids, but found an interaction whereby black patients who exhibited 'challenging' behaviour (such as belligerence and asking for a specific opioid) were more likely to be prescribed opioids than those who did not, an effect possibly due to a racial stereotype [ 43]. Another study that failed to find implicit race bias suggested that this was due to the setting of the study in an inner-city clinic with high levels of black patients and the fact that many physicians were born outside the US [ 24]. Finally, one study that found no evidence of racial bias in prescription of opioid analgesics presented each participant with three vignettes depicting patients of three different ethnicities, thus probably alerting them to the objective of the study [ 40].

The interaction effects between different patient characteristics in assumption studies are varied and a few are surprising. The authors of one study expected that physicians would be less likely to prescribe a higher dose of opioids to black patients who exhibited challenging behaviours; in fact, physicians were more likely to prescribe higher doses of opioids to challenging black patients, yet slightly less likely to do so to white patients exhibiting the same behaviour. Sometimes significant effects on the responses to the vignette of a patient characteristic, e.g. race, are only found when the interaction between gender and race or SES and race is examined. For example, physicians in one study were less certain of the diagnosis of coronary heart disease for middle-aged women, who were thus twice as likely to receive a mental health diagnosis than their male counterparts [ 34]. In another, low SES Latinas and blacks were more likely to have intrauterine contraception recommended than low SES whites, but there was no effect of race for high SES patients [ 39].

Implicit bias affects clinical judgement and behaviour

Three studies found a significant correlation between high levels of physicians' implicit bias against blacks on IAT scores and interaction that was negatively rated by black patients [ 23, 24, 44] and, in one study, also negatively rated by external observers [ 23]. Four studies examining the correlation between IAT scores and responses to clinical vignettes found a significant correlation between high levels of pro-white implicit bias and treatment responses that favoured patients specified as white [ 42, 45- 47]. In one study, implicit prejudice of nurses towards injecting drug users significantly mediated the relationship between job stress and their intention to change jobs [ 48].

Twenty out of 25 assumption studies found that some kind of bias was evident either in the diagnosis, the treatment recommendations, the number of questions asked of the patient, the number of tests ordered, or other responses indicating bias against the characteristic of the patient under examination.

Determinants of bias

Socio-demographic characteristics of physicians and nurses (e.g. gender, race, type of healthcare setting, years of experience, country where medical training received) are correlated with level of bias. In one study, male staff were significantly less sympathetic and more frustrated than female staff with self-harming patients presenting in A&E [ 26]. Black patients in the US -but not the UK- were significantly more likely to be questioned about smoking than white [ 28]. In another study, international medical graduates rated the African-American male patient in the vignette as being of significantly lower SES than did US graduates [ 38]. One study found that paediatricians held less implicit race bias compared with other MDs [ 47].

Correlations between explicit and implicit attitudes varied depending on the type of bias and on the kind of explicit questions asked. For instance, implicit anti-fat bias tends to correlate more with an explicit anti-fat bias than racial bias, where explicit and implicit attitudes often diverge significantly. Because physicians' and nurses' implicit attitudes diverged frequently from their explicit attitudes, explicit measures cannot be used alone to measure the presence of bias among healthcare professionals.

Discussion

A variety of studies, conducted in various countries, using different methods, and testing different patient characteristics, found evidence of implicit biases among healthcare professionals and a negative correlation exists between level of implicit bias and indicators of quality of care. The two most common methods employed were the assumption method and the IAT, the latter sometimes combined with another measure to test for correlations with the behaviour of healthcare professionals.

Our study has several limitations. Four studies included participants who were not trained physicians or nurses and failed to report separate results for these categories of participants [ 42, 44, 49, 50]. Since either the majority of participants were qualified physicians and nurses, or were other health care professionals involved in patient care, we included these studies despite this limitation. Excluding them would not have changed the conclusions of this paper. In addition, we initially centred our research on studies employing implicit measures recognised in psychology, but the majority of the included studies in the final review used the assumption method. However, the limitations imposed by the lack of consistency in keywords and categorization of articles actually worked in our favour here, enabling us to capture a variety of methods and thus to consider including the assumption method. Scanning the references of the articles that were initially retained and repeating this process until there were no new articles helped us to capture further pertinent articles. From the degree of cross-referencing we are confident that we succeeded in identifying most of the relevant articles using the assumption method.

Publication bias could limit the availability of results that reveal little or no implicit bias among healthcare professionals. Moreover, eight articles appeared to refer to the same data collected in a single cross-country comparison study [ 27- 32, 34, 35] and a further two articles analysed the same data [ 45, 47]. The sum of 42 articles thus can give the impression that more research has been carried out on more participants than is the case. The solidity of data revealing high levels of implicit bias among the general population suggest that this is unlikely to have invalidated the conclusion that implicit bias is present in healthcare professionals [ 6, 7].

However, our decision to exclude studies that involved students rather than fully-trained healthcare professionals meant that we did not include a study conducted on medical students that showed no significant association between implicit bias and clinical assessments [ 51]. Several studies post 2013 (thus after our cut-off date) have also indicated a null relationship between levels of implicit bias and clinical decision-making [ 52- 54]. The scientific community working in this area agrees that the relationship between levels of implicit bias in healthcare professionals and clinical decision-making is complex and that there is currently a lack of good evidence for a direct negative influence of biases [ 16, 17]. As our review shows, there is clearer evidence for a relationship between implicit bias and negative effects on clinical interaction [ 23, 24, 44]. While this may not always translate into negative treatment outcomes, the relationship between a healthcare professional and her patient is essential to providing good treatment, thus it seems likely that the more negative the clinical interaction, the worse the eventual treatment outcome (not to mention the likelihood that the patient will consult healthcare services for future worries or problems). This is where the bulk of future research should be concentrated.

The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. They also highlight the pertinence of work in feminist theory on 'intersectionality', a term for the distinctive issues that arise when a person belongs to multiple identity categories that bring disadvantage, such as being both black and female [ 55]. For instance, one study only found evidence of bias against low SES Latina patients, not against high SES Latinas, illustrating how belonging to more than one category (here, both low SES and Latina) can have negative effects that are not present if membership of one category is eliminated (here, low SES) [ 39]. Class may trump race in some circumstances so that being high SES is more salient than being non-white. One criticism of mainstream feminism by theorists who work on intersectionality is that pertinent issues are unexplored because of the dominance of high SES white women in feminist theory. Using our example from the review, high SES Latina women may not experience the same prejudice as low SES Latina women and thus may falsely assume that there is no prejudice against Latina women tout court in this context. This could be frustrating for low SES Latina women who have unrecognized lived experiences of prejudice in a clinical setting.

In some studies, the attitudes of patients towards healthcare professionals were recorded and used to evaluate clinical interaction [ 23, 24, 44]. It is important to remember that patients also may come to a clinical interaction with biases. In these cases, the biases of one participant may trigger the biases of the other, magnifying the first participant's biased responses and leading to a snowball effects [ 56]. Past experience of discrimination may mean that a patient may come to an interaction with negative expectations [ 57].

Our findings in the review suggest that the relationship between training and experience and levels of implicit bias is mixed. In one study, increased contact with patients with Hepatitis C virus was associated with more favourable explicit attitudes, yet more negative implicit attitudes towards intravenous drug users [ 49]. Another study demonstrated that nursing students were less prejudiced, more willing to help and desired more social interaction with patients with brain injury, when compared with qualified nurses [ 58]. Exposure to communication skills training was not associated with lower race-IAT scores for physicians [ 23]. However, individuals with mental health training demonstrated more positive implicit and explicit evaluations of people with mental illness than those without training [ 42]. Yet in the same study, graduate students had more positive implicit attitudes towards the mentally ill than mental health professionals.

We included all types of implicit bias in our review, not only race bias, partly in an effort to capture non-US studies, hypothesising that the focus on race in the US leaves fewer resources for investigation into other biases. It is possibly the case that a wider range of biases were investigated in non-US countries, but there is not enough evidence to deduce this from our review alone. For instance, two British studies examine bias against brain-injured patients who are perceived as having contributed to their injury [ 58, 59], and two Australian studies looked at bias against intravenous drug users [ 48, 49], but the sample size of studies is too small to warrant drawing any conclusions from this.

Is it possible that there are implicit associations that are justified because they are based on prevalence data for diseases? One study in our review aimed to test the statistical discrimination hypothesis by asking physicians to estimate the prevalence data among males and females for coronary heart disease in addition to presenting them with vignettes of a female or male coronary heart disease patient. It found that 48% of physicians were inconsistent in their population-level and individual level assessments and that the physicians' gender-based population prevalence assessments were not associated with the certainty of their diagnosis of coronary heart disease. There was no evidence to support the theory of statistical discrimination as an explanation for why physicians were less certain of their diagnoses of CHD in women [ 36]. Another exploratory study looked at the diseases that were stereotypically associated with African-Americans and found that many diseases were associated with African-Americans that did not match prevalence data, such as drug abuse [ 20]. The danger in these cases is that a physician may apply a group-level stereotype to an individual and fail to follow-up with a search for individuating information.

Impartial treatment of patients by healthcare professionals is an uncontroversial norm of healthcare. Implicit biases have been identified as one possible factor in healthcare disparities and our review reveals that they are likely to have a negative impact on patients from stigmatized groups. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics. For instance, explicit anti-fat bias was found to be prevalent among healthcare professionals [ 60]. Since weight can be relevant to diagnosis and treatment, it is understandable that it is salient. It is nonetheless disturbing that healthcare professionals exhibit the same explicit anti-fat attitudes prevalent in the general population.

The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. These studies provide some evidence for a relationship between bias as measured by the IAT and behaviour by clinicians that may contribute to healthcare disparities. More studies using real-world interaction measures would be helpful because studies using vignettes remain open to the criticism that they do not reveal the true behaviour of healthcare professionals. In this respect, the three studies using measures of physician-patient interaction are exemplary [ 22- 24], in particular when using independent evaluators of the interactions [ 23]. Overall, our review reveals the need for discussion of methodology and for more interaction between different literatures that focus on different biases.

Conclusion

Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. In addition to addressing implicit biases, measures need to be taken to raise awareness of the potential conflict between holding negative explicit attitudes towards some patient characteristics, such as obesity, and committing to a norm to treat all patients equally.

Our review reveals that this is an area in need of more uniform methods of research to enable better comparison and communication between researchers interested in different forms of bias. Important avenues for further research include examination of the interactions between patient characteristics, and between healthcare professional and patient characteristics, and of possible ways in which to tackle the presence of implicit biases in healthcare.

Acknowledgements

Not applicable. Only the two authors were implicated in the review.

Funding

This work was carried out with the support of grants from the Swiss National Science Foundation under grants numbers: PP00P3_123340 and 32003B_149407.

Availability of data and materials

The search strategy is available in the Appendix to the paper.

Authors' contributions

Both authors discussed to select the databases and decide on the research question, based on CF's knowledge of the field of implicit bias and SH's knowledge of systematic reviews and bioethics literature. CF compiled the key words for the search strategy with constant advice and input from SH. CF drafted the inclusion criteria and received constant input on this from SH: CF carried out the search and downloaded the relevant articles to be scrutinised. CF and SH both independently read all the initial titles to select which were relevant, then the abstracts, and then the final included articles and discussed at each stage to resolve any disagreements. CF drafted the initial tables including the information from the studies and this was revised by SH. SH particularly revised the statistical methods used by the studies and both reviewed their methodology. CF drafted the manuscript and it was revised with comments by SH a number of times until both authors were satisfied with the manuscript. Both authors read and approved the final manuscript.

Competing interest

The authors declare that they have no competing interests.

Ethics approval and consent to participate

Not applicable.

Appendix 1

Search Strategy

Pubmed

PsychINFO and PsychARTICLE

CINAHL

Footnotes

¹ There are conceptual problems with this distinction as used in psychology that have been pointed out by philosophers, but we will ignore these for the purposes of this review.

² Interestingly, physicians were also asked for how they expected their colleagues to rate the vignette, and in these ratings there was a negative bias towards both patients from Ghana and from Serbia.

³ Bias against patients who are seen as contributing to their injury initially seems to be an odd category compared to the more familiar ones of race and gender. Clinicians may treat brain injured patients differently if they are somehow seen as 'responsible' for their injury, for instance, if they were engaging in risk-taking behaviour such as drug taking. Our review was intended to capture studies such as these that identify biases that are specific to clinical contexts and thus of particular interest to clinicians.

Contributor Information

Chloë FitzGerald, Phone: +34 652 447 428, Email: hc.eginu@dlaregztif.eolhc.

Samia Hurst, Email: hc.eginu@tsruh.aimas.

References

1. Holroyd J, Sweetman J. The Heterogeneity of Implicit Bias. In Brownstein, Michael, Saul, Jennifer, editors. Implicit Bias and Philosophy, Volume 1: Metaphysics and Epistemology 1. Oxford: Oxford University Press; 2016. p. 80-103.

2. Blair IV, Steiner JF, Havranek EP. Unconscious (implicit) bias and health disparities: where do we go from here? Perm J. 2011;15:71. [[ PMC free article] [ PubMed] Google Scholar]

4. Louise A. Bias: Friend or Foe? Reflections on Saulish Skepticism. In Brownstein, Michael, Saul, Jennifer, editors. Implicit Bias and Philosophy, Volume 1: Metaphysics and Epistemology 1. Oxford: Oxford University Press; 2016. p. 157-190.

12. De-Shalit A, Wolff J. Disadvantage. Oxford: Oxford University Press; 2007. [ Google Scholar]

16. Zestcott, C. A., Blair, I. V. & Stone, J. Examining the presence, consequences, and reduction of implicit bias in health care: A narrative review. Group Process Intergroup Relat. 2016. doi:10.1177/1368430216642029. [ PMC free article] [ PubMed]

19. De Houwer J, Moors A. How to define and examine the implicitness of implicit measures. In Wittenbrink B, Schwartz N. (eds.). Implicit measures of attitudes: Procedures and controversies. New York: Guilford Press; 2007. pp. 179-194.

27. Arber S, et al. Influence of patient characteristics on doctors' questioning and lifestyle advice for coronary heart disease: a UK/US video experiment. Br J Gen Pract. 2004;54:673-678. [[ PMC free article] [ PubMed] Google Scholar]

29. Lutfey KE, et al. Diagnostic certainty as a source of medical practice variation in coronary heart disease: results from a cross-national experiment of clinical decision making. Med Decis Making. 2009;29(5):606-18. [ PMC free article] [ PubMed]

51. Haider AH, et al. Association of unconscious race and social class bias with vignette-based clinical assessments by medical students. JAMA. 2011;306:942-951. [[ PMC free article] [ PubMed] Google Scholar]

57. Dominicé Dao M. Vulnerability in the clinic: case study of a transcultural consultation. J Med Ethics. 2016. doi:10.1136/medethics-2015-103337. [ PubMed]

64. Chow LY, Kam WK, Leung CM. Attitudes of healthcare professionals towards psychiatric patients in a general hospital in Hong Kong. J Psychiatry. 2007;17(1):3-9.

Articles from BMC Medical Ethics are provided here courtesy of BMC

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Implicit bias in healthcare professionals: a systematic review

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Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display ...

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Connection: This image shows how our different experiences (the place where the people are standing) cause disagreements.

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Connection: The song "This is America" talks a lot about discrimination and noticing it in America. Noticing discrimination is caused by people first experiencing it, and then calling it out. This discrimination is caused by bias and is reflected in how we treat different people.

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Connection: This image shows the Ukraine war that is going on right now. It may have been caused by Russians wanting a reunited Soviet Union, because Russia benefited from it. Ukrainians who had bad experiences in the Soviet Union likely were the ones who wanted independence in the first place, and are the ones who are resisting Russian influence now.

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Connection: This refers to the original wanting of independence for the United States. People wanted independence because they experienced unfair taxes and other restrictions due to the British, which made them not like the British.

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Connection: This article talks about bias, which is caused by experiences, as discussed in other posts. This "barrier" is where people treat blacks differently from others due to this bias.

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Black Americans overwhelmingly say unconscious bias is a major barrier in their lives

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A national poll of Black opinion. Read more stories in this series. Black people say unconscious racial bias has been a major barrier in their lives, posing as …

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Connection: This article also discusses implicit bias, which as explained in other posts, is caused by our experiences and causes us to treat others differently.

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Implicit bias can be found throughout many areas of the law, but it has perhaps been discussed in legal literature most often in the area of jury selection. The Supreme Court decision Batson v. Kentucky in 1986 addressed the question of whether the prosecutor's use of peremptory challenges to exclude the four black from the jury violated Batson's sixth and Fourteenth Amendment rights to a fair jury trial and his Fourteenth Amendment rights to equal protection of the laws. Justice Powell held that racial discrimination in the selection of jurors not only deprives the accused of important rights during a trial, but also is devastating to the community at large because it "undermines public confidence in the fairness of our system of justice." Although the issue in Batson dealt with explicit bias, it is still important in understanding the seriousness of bias in jury selection and its potential impact on the outcomes.

Because implicit bias has not been recognized by the courts, "it cannot yet serve as an appropriate basis for challenging jurors or objections under Batson." 1 Instead, the courts are limited to, and active in, educating lawyers and judges to recognize potential implicit bias in jury selection.

Although generally courts are not permitted to examine jury deliberations or juror motivations, in an opinion decided on March 6, 2017, the Supreme Court held that "where a juror makes a clear statement that indicates he or she relied on racial stereotypes or animus to convict a criminal defendant, the Sixth Amendment requires that the no-impeachment rule give way in order to permit the trial court to consider the evidence of the juror's statement and any resulting denial of the jury trial guarantee." Thus, the Court continues to look only at overt expressions of racism as a test for constitutional rights: "For the inquiry to proceed, there must be a showing that one or more jurors made statements exhibiting overt racial bias that cast serious doubt on the fairness and impartiality of the jury's deliberations and resulting verdict." Pena-Rodriguez v. Colorado, slip op. at 17.

For additional information, see:

1. § 22:6.Explicit and implicit bias, Jury Selection Strategy and Science § 22:6 (3d ed.)

2. Anna Roberts, (Re)forming the Jury: Detection and Disinfection of Implicit Juror Bias, 44 Conn. L. Rev. 827 (2012)

3. Judge Mark W. Bennett, Unraveling the Gordian Knot of Implicit Bias in Jury Selection: The Problems of Judge-Dominated Voir Dire, the Failed Promise of Batson, and Proposed Solutions, 4 Harv. L. & Pol'y Rev. 149, (2010)

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Research Guides: Implicit Bias in the Law: In the Courts

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Implicit bias can be found throughout many areas of the law, but it has perhaps been discussed in legal literature most often in the area of jury selection. The Supreme Court decision Batson v.

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Connection: This article also discusses implicit bias, which as explained in other posts, is caused by our experiences and causes us to treat others differently.

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A little misbehavior at school can land kids in hot water. How much? In many cases, that depends on the color of a student's skin. Black students more frequently get detention for being disruptive or loud. White students acting the same way are more likely to get off with a warning.

That doesn't mean that teachers and administrators are racist. At least, most don't intend to be unfair. Most want what's best for all students, no matter what their race or ethnicity might be. And they usually believe that they treat all students equally.

But all people harbor beliefs and attitudes about groups of people based on their race or ethnicity, gender, body weight and other traits. Those beliefs and attitudes about social groups are known as biases. Biases are beliefs that are not founded by known facts about someone or about a particular group of individuals. For example, one common bias is that women are weak (despite many being very strong). Another is that blacks are dishonest (when most aren't). Another is that obese people are lazy (when their weight may be due to any of a range of factors, including disease).

People often are not aware of their biases. That's called an unconscious or implicit bias. And such implicit biases influence our decisions whether or not we mean for them to do so.

Having implicit biases doesn't make someone good or not-so-good, says Cheryl Staats. She's a race and ethnicity researcher at Ohio State University in Columbus. Rather, biases develop partly as our brains try to make sense of the world.

Our brains process 11 million bits of information every second. (A bit is a measure of information. The term is typically used for computers.) But we can only consciously process 16 to 40 bits. For every bit that we're aware of, then, our brains are dealing with hundreds of thousands more behind the scenes. In other words, the vast majority of the work that our brains do is unconscious. For example, when a person notices a car stopping at a crosswalk, that person probably notices the car but is not consciously aware of the wind blowing, birds singing or other things happening nearby.

To help us quickly crunch through all that information, our brains look for shortcuts. One way to do this is to sort things into categories. A dog might be categorized as an animal. It might also be categorized as cuddly or dangerous, depending on the observers' experiences or even stories that they have heard.

As a result, people's minds wind up lumping different concepts together. For example, they might link the concept of "dog" with a sense of "good" or "bad." That quick-and-dirty brain processing speeds up thinking so we can react more quickly. But it also can allow unfair biases to take root.

"Implicit biases develop over the course of one's lifetime through exposure to messages," Staats says. Those messages can be direct, such as when someone makes a sexist or racist comment during a family dinner. Or they can be indirect - stereotypes that we pick up from watching TV, movies or other media. Our own experiences will add to our biases.

The good news is that people can learn to recognize their implicit biases by taking a simple online test. Later, there are steps people can take to overcome their biases.

Can people be 'colorblind'?

"People say that they don't 'see' color, gender or other social categories," says Amy Hillard. However, she notes, they're mistaken. Hillard is a psychologist at Adrian College in Michigan. Studies support the idea that people can't be truly "blind" to minority groups, she notes. Everyone's brain automatically makes note of what social groups other people are part of. And it takes only minor cues for our minds to call up, or activate, cultural stereotypes about those groups. Those cues may be a person's gender or skin color. Even something as simple as a person's name can trigger stereotypes, Hillard says. This is true even in people who say they believe all people are equal.

Many people are not aware that stereotypes can spring to mind automatically, Hillard explains. When they don't know, they are more likely to let those stereotypes guide their behaviors. What's more, when people try to pretend that everyone is the same - to act as though they don't have biases - it doesn't work. Those efforts usually backfire. Instead of treating people more equally, people fall back even more strongly onto their implicit biases.

Gerry Lauzon/Flickr (CC-BY 2.0)

Race is one big area in which people may exhibit bias. Some people are explicitly biased against black people. That means they are knowingly racist. Most people are not. But even judges who dedicate their lives to being fair can show implicit bias against blacks. They have tended, for instance, to hand down harsher sentences to black men than to white men committing the same crime, research has shown.

And whites aren't the only people who have a bias against blacks. Black people do, too - and not just in terms of punishment.

Consider this 2016 study: It found teachers expect white students to do better than black ones. Seth Gershenson is an education policy researcher at American University in Washington, D.C. He was part of a team that studied more than 8,000 students and two teachers of each of those students.

They looked at whether the teacher and student were the same race. And about one in every 16 white students had a non-white teacher. Six in every 16 black students had a teacher who was not black. Gershenson then asked whether the teachers expected their students to go to - and graduate from - college.

White teachers had much lower expectations for black students than black teachers did. White teachers said they thought a black student had a one-in-three chance of graduating from college, on average. Black teachers of those same students gave a much higher estimate; they thought nearly half might graduate. In comparison, nearly six in 10 teachers - both black and white - expected white students to complete a college degree, Gershenson says. In short, both sets of teachers showed some bias.

"We find that white teachers are significantly more biased than black teachers," he notes. Yet the teachers were not aware they were biased in this way.

Does gender matter?

Implicit bias is a problem for women, as well. Take, for instance, the unfounded claim that women aren't good at science, technology, engineering or math (STEM). Women can (and frequently do) excel in all of these areas. In fact, women earn 42 percent of science and engineering PhDs. Yet only 28 percent of people who get jobs in STEM fields are women. And women who do work in STEM tend to earn less than do men of equal rank. They also receive fewer honors and are promoted less frequently than the men they work with.

USAID Asia/Flickr (CC BY-NC 2.0)

This gender difference in hiring and promotion may be due partly to a bias in how recommendation letters are written. Such letters help employers know how well a person has done in a past job.

In one 2016 study, researchers at Columbia University in New York City probed what was said in those recommendations. The team examined 1,224 letters of recommendation written by professors in 54 different countries. Around the world, both men and women were more likely to describe male students as "excellent" or "brilliant." In contrast, letters written for female students described them as "highly intelligent" or "very knowledgeable." Unlike the terms used for men, these phrases do not set women apart from their competition, the researchers say.

Biases against women don't only happen in the sciences. Research by Cecilia Hyunjung Mo finds that people are biased against women in leadership positions, too. Mo is a political scientist at Vanderbilt University in Nashville, Tenn.

Women make up 51 percent of the U.S. population. Yet they make up only 20 percent of people serving in the U.S. Congress. That's a big difference. One reason for the gap may be that fewer women than men run for political office. But there's more to it, Mo finds.

In one 2014 study, she asked 407 men and women to take a computerized test of implicit bias. It's called the implicit association test, or IAT. This test measures how strongly people link certain concepts, such as "man" or "woman," with stereotypes, such as "executive" or "assistant."

During the test, people are asked to quickly sort words or pictures into categories. They sort the items by pressing two computer keys, one with their left hand and one with their right. For Mo's test, participants had to press the correct key each time they saw a photo of a man or a woman. They had to choose from the same two keys each time they saw words having to do with leaders versus followers. Halfway through the tests, the researchers switched which concepts were paired together on the same key on the keyboard.
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People tended to respond faster when photos of men and words having to do with leadership shared the same key, Mo found. When photos of women and leadership-related words were paired together, it took most people longer to respond. "People typically found it easier to pair words like 'president,' 'governor' and 'executive' with males, and words like 'secretary,' 'assistant' and 'aide' with females," Mo says. "Many people had a lot more difficulty associating women with leadership." It wasn't only men who had trouble making that association. Women struggled, too.

Mo also wanted to know how those implicit biases might be related to how people behave. So she asked the study participants to vote for fictional candidates for a political office.

She gave each participant information about the candidates. In some, the male candidate and the female candidate were equally qualified for the position. In others, one candidate was more qualified than the other. Mo's results showed that people's implicit biases were linked to their voting behavior. People who showed stronger bias against women in the IAT were more likely to vote for the male candidate - even when the woman was better qualified.
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U.S. Library of Congress; Wikimedia/Office of U.S. Sen. Barbara Mikulski

Size matters

One of the strongest social biases is against the obese. Chances are, you harbor a dislike for people who are severely overweight, says Maddalena Marini. She is a psychologist at Harvard University in Cambridge, Mass. Implicit weight bias seems universal, she says. "Everyone possesses it. Even people who are overweight or obese."

To reach that conclusion, she and her team used data from Harvard's Project Implicit website. This site allows people to take an IAT. There are currently 13 types of these tests of implicit bias on the site. Each probes for a different type of bias. More than 338,000 people from around the world completed the weight-bias test between May 2006 and October 2010, the time leading up to Marini's study. This IAT was similar to the one for race. But it asked participants to categorize words and images that are associated with good and bad, and with thin and fat.

After taking the IAT, participants answered questions about their body mass index. This is a measure used to characterize whether someone is at a healthy weight.
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Maddalena Marini

Marini found that heavier people have less bias against people who are overweight or obese. "But they still prefer thin people, on average," she notes. They just don't feel this way as strongly as thin people do. "Overweight and obese people tend to identify with and prefer their weight group," Marini says. But they may be influenced by negativity at the national level that leads them to prefer thin people.

People from 71 nations took part in the study. That allowed Marini to examine whether an implicit bias against heavy people was linked in any way to whether weight problems were more common in their nation. To do this, she combed public databases for weight measurements from each country. And nations with high levels of obesity had the strongest bias against the obese, she found.

She's not sure why obese nations have such a strong implicit bias against overweight people. It could be because those nations have more discussions about the health problems associated with obesity, Marini says. It may also come from people seeing more ads for "diet plans, healthy foods and gym memberships aimed at decreasing obesity," she notes. Or perhaps people in these countries simply see that people with high social status, good health and beauty tend to be thin.

Weight bias seems to be more commonly accepted than race and gender bias. In other words, people tend to feel freer to verbally express their weight bias. That's according to a 2013 study led by Sean Phelan. He is a policy researcher at the Mayo Clinic in Rochester, Minn. Medical students often express weight bias openly, he finds. And that can translate into poorer health care for people who are severely overweight. "Health-care providers display less respect for obese patients," he reports. He also notes that research shows that "physicians spend less time educating obese patients about their health" than they do with patients who aren't obese.

Embracing diversity breaks down bias

Antonya Gonzalez is a psychologist in Canada at the University of British Columbia in Vancouver. "We may think we treat everyone equally," she says, but "unconscious biases can shape our behavior in ways we aren't always aware of." Knowing that you might be biased "is the first step to understanding how you treat other people - and trying to change your own behavior," she says.

Gonzalez knows about changing behavior. In a 2016 study with 5- to 12-year-old children, she found that their implicit bias against black people could change. The children were told positive stories about people, such as a firefighter who works hard to protect his community. Some children saw a photo of a white man or woman while they heard the story. Others saw a photo of a black person. After the story, each child took a race IAT. Children who learned about a black person were less biased when they took the test, compared with children who had heard about a white person.

"Learning about people from different social groups who engage in positive behaviors can help you to unconsciously associate that group with positivity," Gonzalez says. "That's part of the reason why diversity in the media is so essential," she notes. It helps us to "learn about people who defy traditional stereotypes."

Hillard at Adrian College also found that diversity training can help adults counteract a bias against women. "The first step is awareness," she says. Once we are aware of our biases, we can take steps to block them.

It also helps to step back and think about whether stereotypes could possibly provide good information to act on, she notes. Could a stereotype that is supposed to be true of a large portion of the population, such as "all women" or "all people of color," truly be accurate?

The key is to embrace diversity, says Staats - not to pretend it doesn't exist. One of the best ways to do this is to spend time with people who are different than you. That will help you see them as individuals, rather than part of a stereotypical group.

"The good news is that our brains are malleable," she says. "We are able to change our associations."

Power Words
More About Power Words

average (in science) A term for the arithmetic mean, which is the sum of a group of numbers that is then divided by the size of the group.

behavior The way a person or other organism acts towards others, or conducts itself.

bias The tendency to hold a particular perspective or preference that favors some thing, some group or some choice. Scientists often "blind" subjects to the details of a test (don't tell them what it is) so that their biases will not affect the results.

body mass index (BMI) A person's weight in kilograms divided by the square of his or her height in meters. BMI can be used to evaluate if someone is overweight or obese. However, because BMI does not account for how much muscle or fat a person has, it is not an accurate measure.

Congress The part of the U.S. federal government charged with writing laws, setting the U.S. budget, and confirming many presidential appointments to the courts, to represent the U.S. government interests overseas and to run administrative agencies. The U.S. Congress is made of two parts: the Senate, consisting of two members from each state, and the House of Representatives, which consists of a total of 435 members, with at least one from each state (and dozens more for the states with the biggest populations).

diet The foods and liquids ingested by an animal to provide the nutrition it needs to grow and maintain health. (verb) To adopt a specific food-intake plan for the purpose of controlling body weight.

diversity (in biology) A range of different life forms.

engineering The field of research that uses math and science to solve practical problems.

ethnicity (adj. ethnic) The background of an individual based on cultural practices that tend to be associated with religion, country (or region) of origin, politics or some mix of these.

gender The attitudes, feelings, and behaviors that a given culture associates with a person's biological sex.

high school A designation for grades 9 through 12 in the U.S. system of compulsory public education. High-school graduates may apply to colleges for further, advanced education.

implicit bias To unknowingly hold a particular perspective or preference that favors some thing, some group or some choice - or, conversely, holds some unrecognized prejudice against it.

malleable Something whose shape can be altered, usually by hammering or otherwise deforming with pressure. (in social science) Attitudes or behaviors that can be changed with social pressure or logic.

media (in the social sciences) A term for the ways information is delivered and shared within a society. It encompasses not only the traditional media - newspapers, magazines, radio and television - but also Internet- and smartphone-based outlets, such as blogs, Twitter, Facebook and more.

obesity (adj. obese) Extreme overweight. Obesity is associated with a wide range of health problems, including type 2 diabetes and high blood pressure.

online A term that refers to things that can be found or done on the internet.

overweight A medical condition where the body has accumulated too much body fat. People are not considered overweight if they weigh more than is normal for their age and height, but that extra weight comes from bone or muscle.

political scientist Someone who studies or deals with the governing of people, largely by elected officials and governments.

population (in biology) A group of individuals from the same species that lives in the same area.

psychologist A scientist or mental-health professional who studies the human mind, especially in relation to actions and behavior.

social (adj.) Relating to gatherings of people; a term for animals (or people) that prefer to exist in groups. (noun) A gathering of people, for instance those who belong to a club or other organization, for the purpose of enjoying each other's company.

STEM An acronym (abbreviation made using the first letters of a term) for science, technology, engineering and math.

stereotype A widely held view or explanation for something, which often may be wrong because it has been overly simplified.

trait A characteristic feature of something. (in genetics) A quality or characteristic that can be inherited.

Citations

Journal: A.M. Gonzalez et al. Reducing children's implicit racial bias through exposure to positive out-group exemplars. Child Development. Vol. 88, January/February 2017, p. 123. doi: 10.1111/cdev.12582.

Journal: K. Dutt et al. Gender differences in recommendation letters for postdoctoral fellowships in geoscience. Nature Geoscience. Vol. 9, November 2016, p. 805. doi: 10.1038/ngeo2819.

Journal: S. Gershenson et al. Who believes in me? The effect of student-teacher demographic match on teacher expectations. Economics of Education Review. Vol. 52, June 2016, p. 209. doi: 10.1016/j.econedurev.2016.03.002.

Report: C. Staats. Understanding implicit bias: What educators should know. American Educator. Winter 2015-2016.

Report: C. Staats. State of the science: Implicit bias review 2014. Kirwan Institute for the Study of Race and Ethnicity.

Journal: C.H. Mo. The consequences of explicit and implicit gender attitudes and candidate quality in the calculations of voters. Political Behavior. Vol. 37, June 2015, p. 357. doi: 10.1007/s11109-014-9274-4.

Journal: S.M. Jackson, A.L. Hillard and T.R. Schneider. Using implicit bias training to improve attitudes toward women in STEM. Social Pshycology of Education. Vol. 17, September 2014, p. 419. doi: 10.1007/s11218-014-9259-5.

Journal: S.M. Phelan et al. Implicit and explicit weight bias in a national sample of 4,732 medical students: The medical student CHANGES study. Obesity. Vol. 22, April 22, 2014, p. 1201. doi: 10.1002/oby.20687.

Journal: M. Marini et al. Overweight people have low levels of implicit weight bias, but overweight nations have high levels of implicit weight bias. PLOS One. Vol. 8, Published online December 17, 2013, p. e83543. doi: 10.1371/journal.pone.0083543.
Questions for 'Think you're not biased? Think again'
Wordfind (click here)

Alison Pearce Stevens is a former biologist and forever science geek who writes about science and nature for kids. She lives with her husband, their two kids and a small menagerie of cuddly (and not-so cuddly) critters.

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A little misbehavior at school can land kids in hot water. How much? In many cases, that depends on the color of a student's skin. Black students more frequently get detention for being disruptive or loud. White students acting the same way are more likely to get off with a warning.

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Connection: This image refers to the Uighur Turks, and how they are being discriminated against in Turkey. Turkey is also accused of even deporting them. This is caused by people's biases against these Turks, and those are in turn caused by our experiences. This causes people to treat Uighurs differently, by deporting them rather than allowing them to coexist in Turkey.

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When the jurors are discussing about how the old man heard the boy yell out he's going to kill his father and saw him run down the stairs, the 9th juror who has been pretty quiet chimes in saying that the old man could have testified for attention.

"9TH JUROR: Attention, maybe." (Rose 43)

This brings up a whole new perspective for the jurors to think about. The 9th juror later states how he had been analyzing the old man during his testimony. Things like the way he walked, and how he dressed gave the 9th juror an impression. This impression did not come from nothing however, because the 9th juror is also an older man and would be able to understand another older man a lot better than the younger jurors.

This all ties into our experiences influencing how we perceive others. Since the 9th juror was an older man he would have more similarities and commonalities with the old man who testified. When compared to the younger jurors, the 9th jurors new perspective came from his experiences throughout his life. These experiences influences how he first perceived the old man allowing him to give the jurors a new perspective to think about.

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- Very formal & impactful language
- Makes people feel emotional - makes people feel bad for Gorman at the beginning, then makes people feel an obligation to better their society to help people like Gorman
- Reflects education
- Spreads utopian ideals near the end
- Ornate but clear to have the largest impact

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C. I think her views on humanity is a mixture of both optimistic for the future but pessimistic of the past. Throughout this passage she talks about humans have to be unified and we are getting there keeping our differences aside. But she is also pessimistic about humans based on the past, which when she talks forces that caused a civil war and the slavery which was in US.
D. I think Gorman's worldview compares Rose's view. Gormans view is saying that the future can hold hope and fix the mistake that happened in the past. Roses is also similar to this as we see a advancement in the court system which could also be implied to world. His view was showing that the world worked with a bias, based on what they influenced, but to the end it showed that they were letting go of that bias, which shows and advancement and faith in humanity.

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C) I think Gorman is very optimistic about humanity's future, while she is more neutral about the past. She believes that in the past, people have been very resistant to change, but they have still made some progress. For example, Gorman talks about how she would have been a slave in the past but instead became the reciter for the president. However, she still believes that it is not enough. For the future, Gorman explains that if the current generations do well, we can make a bright future for others to come. She talks about how we have a lot of power and can change the bad things about the present, and humanity can become a lot better in the long run.

D) Gorman's worldview contrasts from Rose's, because Gorman takes a more optimistic stance, while Rose takes a more pessimistic stance. However, they do have some similarities, in Gorman being pessimistic and Rose being optimistic at times. First, Gorman explains her hopes for a utopian future, and that we have made some progress in the past. In contrast, Rose focuses on the bad parts of the present, in which people from the slums, for example, are being discriminated against, even in court. However, similarly to Gorman, Rose also shows the good in society and that it can be reformed through Juror 8, and his ability to convince the entire jury. Finally, Gorman is a little pessimistic about the past, saying that we have not made a huge amount of progress, but rather a limited amount. This is similar to Rose's main commentary about his present (which is our past).

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C. I think that Gorman is optimistic towards society, as when she talks about our future, she says that we will prevail and break through these hard times. She does bring up a lot of bad things that happened in our past, but it doesn't matter as we will learn from these mistakes and build on top of them.

D. Gorman is very hopeful for our future, while Rose seems to highlight more of the flaws in out society without showing us how to improve upon in or get rid of the problems. They both bring up the bad things that are happening, but Gorman gives us hope while Rose doesn't.

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C. I think Gorman is optimistic about the future of humanity. She speaks about how we need to put our differences aside to create a unified country. Gorman believes that it's up to us to give humanity a better future. She speaks about our country's past, like slavery and our struggles, but she believes that if we come together we can leave behind a better country than the one we were left.

D. I think Gorman's worldview compares to Rose's. Gorman believes we need to set differences aside to create harmony for all. As seen in 12 Angry Men, the jurors put their past and differences aside to come up with a verdict. Gorman explains how victory lies in the connections made not war or violence. Once the 3rd juror divided his past with his son and the boy's case, they were able to come up with the verdict of not guilty. Gorman's and Rose's view suggests to put our differences, past, and biases aside to forge a unified union.

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Poetry Station 9 Personal Reading Diagram

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Poetry Station 9 Personal Reading Diagram

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Create a new document and edit with others at the same time -- from your computer, phone or tablet. Get stuff done with or without an internet connection. Use Docs to edit Word files. Free from Google.

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Solution to Challenges from the Essential Question

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Solution to Challenges from the Essential Question

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We can judge others in bad ways, such as stereotypes, due to our experiences. To prevent this, we can try to spend more time getting to know individuals of the specific group that we are biased towards. This helps us realize that people of a certain "group" (such as race, age, etc.) are all unique in their own ways. This can help break stereotypes by making us see the differences between people of that "group". We also need to be able to identify our biases so that we know what to correct. Therefore, we can be more aware of how we treat different people and notice why we treat them that way. If we recognize a pattern between people with a certain characteristic, we can make sure that we prevent ourselves from stereotyping new people we meet with that characteristic.

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Create a new document and edit with others at the same time -- from your computer, phone or tablet. Get stuff done with or without an internet connection. Use Docs to edit Word files. Free from Google.