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      <title>GEOG 241- Washington County, Oregon by Ashley Gallegos</title>
      <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j</link>
      <description>By: Ashley G, Jeff R, Sonia R, Olivia M, Marouane H, Iliana P, and  Xinyi Y</description>
      <language>en-us</language>
      <pubDate>2025-04-23 13:49:35 UTC</pubDate>
      <lastBuildDate>2025-05-12 20:47:47 UTC</lastBuildDate>
      <webMaster>hello@padlet.com</webMaster>
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         <title></title>
         <author>jeffrossbach</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430390448</link>
         <description><![CDATA[<p>Examining the dependency ratios for Washington County, Oregon, in both 2010 and 2020 reveals a significant amount of information regarding the working class's ability to sustain the dependent population. Starting in 2010, the group most dependent on the working class is the youth and child population, with a dependency ratio of 39.86. The value of 39.86 indicates a moderate level of dependency on the working population, which is still manageable. For the aged population, the dependency ratio is 15.59, which is significantly lower than that of the youth and child population and represents a relatively low value overall. The total dependency ratio for 2010 is 55.45, which is relatively high but overall still manageable by the working population. Compared to the 2010 ratios, the 2020 dependency ratios for Washington County, Oregon, are similar in value to those of 2010, but exhibit slight changes. For example, the youth/child dependency ratio dropped from 39.86 to 35.62, indicating less dependence of the youth/child population on the working class. The aged population, however, experienced an increase in its dependency ratio, rising from 15.59 to 22.30, indicating a rise in the ratio of the aged population to the working population. As a result of the larger increase in the aged dependency ratio, the total dependency ratio increased slightly from 55.45 in 2010 to 57.91 in 2020. The increase in the total dependency ratio is not highly significant and is unlikely to cause a substantial impact on the people of Washington County. However, if the shift towards greater dependence on the working population continues in the coming years, it could become a problem that requires further attention.</p>]]></description>
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         <pubDate>2025-04-29 18:59:54 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430390448</guid>
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         <title>Washing County Oregon, 2010 Population Pyramid</title>
         <author>jeffrossbach</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430462609</link>
         <description><![CDATA[<p>The population pyramid for Washington County, Oregon, in 2010 reveals that most of the population is middle-aged working population, and the youth population. The lowest population in the area is that of the aged population and those who are just becoming part of the working population between 18 and 21 years old. </p>]]></description>
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         <pubDate>2025-04-29 20:13:37 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430462609</guid>
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         <title></title>
         <author>jeffrossbach</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430462842</link>
         <description><![CDATA[<p>Compared to the 2010 population pyramid, there is a larger amount of aged population, particularly in the 70 to 74 year range, along with a drop in the under 5 category for children. These changes could be the result of low migration to and from the area and the natural aging of the population that was already living there. </p>]]></description>
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         <pubDate>2025-04-29 20:13:58 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3430462842</guid>
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         <title>Map: Washington County,Oregon </title>
         <author>ashleyj032505</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3431971438</link>
         <description><![CDATA[]]></description>
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         <pubDate>2025-04-30 17:08:35 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3431971438</guid>
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         <title>Rood Bridge Park </title>
         <author>ashleyj032505</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3431984269</link>
         <description><![CDATA[<p>Here is an image of Rood Bridge Park located in  Washington County, Oregon.</p>]]></description>
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         <pubDate>2025-04-30 17:20:08 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3431984269</guid>
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         <title>Ethnic Changes for Washington County, Oregon; 2010-2020</title>
         <author>soniarosalesrosenthal55</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3443611915</link>
         <description><![CDATA[<p>In analyzing the ethnic changes for Washington County, Oregon between the 2010 and 2020 decennial censuses, the most significant observed changes in percent changes were in the Other Hispanic or Latino populations, Other Asian populations, and White alone. The majority of the population is White alone, and the other two groups that see significant changes do not take up a significant portion of the population, which is why the percentage changes are so high. Though the White alone population is the majority in this county, it observes a decrease in percentage between 2010-2020 by -4.98%. The highest populations, besides White alone, are Hispanic or Latino; specifically Mexican, and Asian, with significant numbers of Asian Indian and Chinese populations. There are even populations of Asians across most of the groups, where there is an overall 54.10% change from 8.38% of the overall population to 11.40%. This included the almost 100% increase in Asian Indian population and a 45.45% increase in the Hmong population, where it almost doubled in size. Hispanic and Latino populations also almost doubled, with an increase from 15.72% of the overall population to 21.68%, which saw a 56.34% change. While the Mexican population holds the majority of the Hispanic and Latino population, the most significant growth in percent change was observed in Dominican, South American and Central American groups. This is due to the originally low population of each group as recorded in the 2010 decennial census, each recording under 1% of the total population in this county, but with increases in populations that are double or triple the 2010 population size by 2020. Other Hispanic or Latino also has a significant percent change, at 225.20%, with a triple in population between 2010-2020 and the second highest percent of total populations in Hispanic and Latino populations for both decennial censuses. The most significant increases in overall populations occur within this group, Other Hispanic and Latino, and Asian, with a range of 23,000-24,000 increase in population. </p>]]></description>
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         <pubDate>2025-05-09 13:42:51 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3443611915</guid>
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         <title>Index of Dissimilarity for White and Blacks, Whites and Asians, Blacks and Asians, and Hispanics and Non-Hispanics for 2010, and 2020.</title>
         <author>xinyiyy</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3445616763</link>
         <description><![CDATA[<p>The difference index is used to calculate the percentage difference between two groups in a specific area. The closer it is to 0, the smaller the difference, and the closer it is to 1, the greater the difference. The formula first determines the two groups to be calculated, for example, calculating whites and blacks. First, use the number of whites in the total population of the area, then calculate the number of blacks divided by the total population of the area, and finally add their values ​​and divide them by 1/2 to calculate the difference value</p><p>More Oregon difference index from 2010 to 2020. The White-Black difference index increased from 0.2430 to 0.2695. The overall increase was small, and there was only a slight segregation between races. This may be due to the impact of housing prices, which led to some groups living in concentrated areas. The White-Asian difference index increased from 0.3331 to 0.3671, showing an upward trend. The White-Asian difference index is higher. Asians generally pay attention to education, so Asians will choose school districts with high square meters when choosing housing. This may have led to an increase in the difference index. The Black-Asian difference index decreased from 0.3068 to 0.2988, with an overall slight decrease. This may be due to the housing policies of some communities, which allow the two races to live together, resulting in a decrease in the difference index. The overall difference index of Hispanics-Non-Hispanic has dropped significantly, from 0.3548 to 0.309. The reason for the greater integration may be that the second-generation Hispanics have received English education since childhood, which makes it easier for them to integrate into the mainstream American group. More Hispanics have left the Hispanic community and integrated into the community of group races, making the difference index more integrated.</p><p>&nbsp;</p>]]></description>
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         <pubDate>2025-05-12 02:27:18 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3445616763</guid>
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      <item>
         <title>Ethnic Changes: Methodology and Assumptions</title>
         <author>mboumila</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3445644934</link>
         <description><![CDATA[<p>To see how each racial or ethnic group’s size in Washington County, Oregon, we first calculate its Percent of Total, found with</p><p><br></p><p><em>(group population ÷ total county population) × 100</em>.</p><p><br></p><p>This turns raw population into percentages so every group is on the same 0 to 100 scale. We assume the census counted every resident only once, that 2010 and 2020 use the same race and ethnicity definitions, and that multiracial responses are handled the same way in both years. Next we measure how fast each group grew or shrank during the decade using Percent Change, given by </p><p><br></p><p><em>[(2020 group population ÷ 2010 group population) − 1] × 100</em>. </p><p><br></p><p>This rate assumes the 2010 baseline is not zero and that no one was reclassified between censuses.</p><p>Applying the two formulas shows how the county actually changed. Between 2010 and 2020, Washington County added about 70,600 people. Roughly two-thirds of that increase came from Hispanic and Latino residents, about 46,900 people, and another third came from Asians, about 24,000. White-alone counts fell by around 20,200, so every bit of net growth came from minority groups. The combined non‑White share of the population rose from 23 percent in 2010 to 36 percent in 2020, a 13-point jump in just one decade. Multiracial responses nearly doubled, now topping 27,000, which explains part of the White decline. Washington County would likely become majority-minority sometime in the mid‑2030s if these growth rates continued. In short, the Percent of Total shows a quickly diversifying county, and the Percent Change singles out Hispanic or Latino and Asian communities as the main engines of that shift.</p>]]></description>
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         <pubDate>2025-05-12 02:43:12 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3445644934</guid>
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         <title>Table 1. Rate of Change for Washington County, Oregon, 2010-2020</title>
         <author>ashleyj032505</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446557740</link>
         <description><![CDATA[<p>The formula being used to calculate the Rate of Change between 2010 and 2020 is r= (Pt2/Pt1 - 1). Pt represents the second or later period while Ptl is the value of the first time period being used. There are two key assumptions one must consider when interpreting the rate of change. First, one must assume that the growth of population is distributed evenly throughout ten years. This indicates that we are calculating a rate of change without accounting for any changes that might occur throughout the decade which is unrealistic. Events such as pandemics, immigration patterns, and economic fluctuations are not taken into consideration. Secondly, one must assume that the population will continue to develop at the same rate it did in the past. Based on table 1, the county's population increased between 2010 and 2020. This growth allows us to infer that a possibility for this could be due to economic opportunities. Washington County is near Portland, Oregon which is a major city within the state. This could have prompted people to move around Portland and relocate in places like Washington County.</p>]]></description>
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         <pubDate>2025-05-12 13:45:26 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446557740</guid>
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         <title>Table 3. Geometric and Exponential Projections for 2030 and 2050 using 2010 and 2020</title>
         <author>oliviamonico1_</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446882853</link>
         <description><![CDATA[<p>In order to find the geometric and exponential projections for 2030 and 2050, one must first calculate the Rate of Change for 2010-2020. The goal of these formulas is to predict the total population of a certain area or county by using past populations.&nbsp; When one calculates the rate of change they can then solve the Projections Formulas since it tells us how fast the population was growing between the two time periods. The Geometric formula is P<sub>t+n</sub>= P<sub>t</sub> (1+r)<sup>n&nbsp; </sup>where Pt represents the starting year, n is the number of years being pushed forward to, r is the rate of change and Pt+n is the predicted population. The formula takes the population of the years we are using to make our prediction and The Geometric Population formula is normally more accurate than the Exponential formula since it is less drastic. Exponential Projections are normally higher than those calculated in the Geometric Projection. The Exponential Projections Formula is <strong>P<sub>t+n</sub> = P<sub>t</sub> e<sup>r*n &nbsp; </sup></strong>which is similar to the Geometric Formula, however, it differs since we are exponentially multiplying. The Exponential Projection formula keeps the population growing continuously. When using “e” our projections reflect the population growth based on the size of the population during the times being used to predict our values.&nbsp;</p><p>From this data, we can gather that over the next few decades, the population of Washington County is going to increase immensely. This can be due to many reasons such as an increase in jobs. Housing in Washington County may also be cheaper than housing in the city, Portland. It is also possible that over the decades, the birthrates in Washington County are higher than the death rates. </p><p><br></p><p><br></p>]]></description>
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         <pubDate>2025-05-12 17:23:20 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446882853</guid>
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         <title>Doubling Times for Exponential Projections</title>
         <author>oliviamonico1_</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446934902</link>
         <description><![CDATA[<p>The doubling time is used after the Exponential Population Projection Formula is used. It helps us to understand population trends and their impacts, longterm. The number reflects the number of years it may take a population to double. If there is a shorter doubling time, there is a faster growth. In our calculations, the doubling time for 2020-2030 is about 52, meaning that it would take an average or steady amount of time for the population to double. However, for 2030-2050, the number is much higher, meaning that it will take longer for the population to double.To compute the doubling time, one must use In2/r where r is the rate of change.</p>]]></description>
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         <pubDate>2025-05-12 18:03:01 UTC</pubDate>
         <guid>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3446934902</guid>
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         <title>Table 8. Entropy Indices for Washington County, Oregon, 2010 and 2020.</title>
         <author>ilianap276</author>
         <link>https://padlet.com/ashleyj032505/9tuho5erjrz4r42j/wish/3447015528</link>
         <description><![CDATA[<p>The Entropy Index measures how evenly populations are distributed. The closer to 1, the more diverse. The formula used to calculate the Entropy Index is:   </p><p><strong><em>&nbsp;          n<br></em>H = - Σ [ (P<sub>k</sub>/P) * ln (P<sub>k</sub>/P) ]<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; k=1</strong></p><p><br/></p><p>Looking at the broad racial category, Washington County, Oregon, has significantly diversified from 2010 to 2020, with the racial entropy increasing from 0.452 to 0.596. </p><p>The Hispanic population rose from 0.378 to 0.403, signaling a small increase and reflecting the rising presence of Hispanic origin groups. Still, Mexicans held the majority in 2010 and 2020, increasing by about 80%. During World War II, the bracero program was an agreement between the US and Mexico. This program aimed to temporarily contract Mexican farmers. This brought many Mexican workers to the US, specifically Washington County. After the program ended, many decided to stay. Though the most consistently diverse group is the Asian population, with an entropy score above 0.93 in both 2010 and 2020. This indicates an even distribution across all Asian ethnic groups. It is the second largest ethnic group after White non-Hispanics. Chinese immigrants played a crucial role in the construction of the transcontinental railroads. After the Chinese Exclusion Act of 1882, Chinese immigration dwindled, as well as other Asian ethnicities, because of xenophobic policies. Until the 1965 Immigration and Nationality Act removed racial discrimination against Asian people, allowing more Asians to immigrate.  </p>]]></description>
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         <pubDate>2025-05-12 19:08:38 UTC</pubDate>
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