5 datasets found
  1. f

    Table_1_Operationalizing racialized exposures in historical research on...

    • frontiersin.figshare.com
    docx
    Updated Jul 6, 2023
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    Marie Kaniecki; Nicole Louise Novak; Sarah Gao; Sioban Harlow; Alexandra Minna Stern (2023). Table_1_Operationalizing racialized exposures in historical research on anti-Asian racism and health: a comparison of two methods.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2023.983434.s001
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    docxAvailable download formats
    Dataset updated
    Jul 6, 2023
    Dataset provided by
    Frontiers
    Authors
    Marie Kaniecki; Nicole Louise Novak; Sarah Gao; Sioban Harlow; Alexandra Minna Stern
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundAddressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism.MethodsWe used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level.ResultsSurname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup.DiscussionSurname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.

  2. WWII: pre-war populations of selected Allied and Axis countries and...

    • statista.com
    Updated Jan 1, 1998
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    Statista (1998). WWII: pre-war populations of selected Allied and Axis countries and territories 1938 [Dataset]. https://www.statista.com/statistics/1333819/pre-wwii-populations/
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    Dataset updated
    Jan 1, 1998
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1938
    Area covered
    World
    Description

    In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

  3. WWII: share of total population lost per country 1939-1945

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). WWII: share of total population lost per country 1939-1945 [Dataset]. https://www.statista.com/statistics/1351638/second-world-war-share-total-population-loss/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    It is estimated that the Second World War was responsible for the deaths of approximately 3.76 percent of the world's population between 1939 and 1945. In 2022, where the world's population reached eight billion, this would be equal to the death of around 300 million people.

    The region that experienced the largest loss of life relative to its population was the South Seas Mandate - these were former-German territories given to the Empire of Japan through the Treaty of Versailles following WWI, and they make up much of the present-day countries of the Marshall Islands, Micronesia, the Northern Mariana Islands (U.S. territory), and Palau. Due to the location and strategic importance of these islands, they were used by the Japanese as launching pads for their attacks on Pearl Harbor and in the South Pacific, while they were also taken as part of the Allies' island-hopping strategy in their counteroffensive against Japan. This came at a heavy cost for the local populations, a large share of whom were Japanese settlers who had moved there in the 1920s and 1930s. Exact figures for both pre-war populations and wartime losses fluctuate by source, however civilian losses in these islands were extremely high as the Japanese defenses resorted to more extreme measures in the war's final phase.

  4. Population of South Korea 1800-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Population of South Korea 1800-2020 [Dataset]. https://www.statista.com/statistics/1067164/population-south-korea-historical/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Korea
    Description

    In 1800, it is estimated that approximately 9.4 million people lived in the region of modern-day South Korea (and 13.8 million on the entire peninsula). The population of this region would remain fairly constant through much of the 19th century, but would begin to grow gradually starting in the mid-1800s, as the fall of the Joseon dynasty and pressure from the U.S. and Japan would end centuries of Korean isolationism. Following the opening of the country to foreign trade, the Korean peninsula would begin to modernize, and by the start of the 20th century, it would have a population of just over ten million. The Korean peninsula was then annexed by Japan in 1910, whose regime implemented industrialization and modernization policies that saw the population of South Korea rising from just under ten million in 1900, to over fifteen million by the start of the Second World War in 1939.

    The Korean War Like most regions, the end of the Second World War coincided with a baby boom, that helped see South Korea's population grow by almost two million between 1945 and 1950. However, this boom would stop suddenly in the early 1950s, due to disruption caused by the Korean War. After WWII, the peninsula was split along the 38th parallel, with governments on both sides claiming to be the legitimate rulers of all Korea. Five years of tensions then culminated in North Korea's invasion of the South in June 1950, in the first major conflict of the Cold War. In September, the UN-backed South then repelled the Soviet- and Chinese-backed Northern army, and the frontlines would then fluctuate on either side of the 38th parallel throughout the next three years. The war came to an end in July, 1953, and had an estimated death toll of three million fatalities. The majority of fatalities were civilians on both sides, although the North suffered a disproportionate amount due to extensive bombing campaigns of the U.S. Unlike North Korea, the South's total population did not fall during the war.

    Post-war South Korea Between the war's end and the late 1980s, the South's total population more than doubled. In these decades, South Korea was generally viewed as a nominal democracy under authoritarian and military leadership; it was not until 1988 when South Korea transitioned into a stable democracy, and grew its international presence. Much of South Korea's rapid socio-economic growth in the late 20th century was based on the West German model, and was greatly assisted by Japanese and U.S. investment. Today, South Korea is considered one of the world's wealthiest and most developed nations, ranking highly in terms of GDP, human development and life expectancy; it is home to some of the most valuable brands in the world, such as Samsung and Hyundai; and has a growing international cultural presence in music and cinema. In the past decades, South Korea's population growth has somewhat slowed, however it remains one of the most densely populated countries in the world, with total population of more than 51 million people.

  5. WWII: share of the male population mobilized by selected countries 1937-1945...

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). WWII: share of the male population mobilized by selected countries 1937-1945 [Dataset]. https://www.statista.com/statistics/1342462/wwii-share-male-mobilization-by-country/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    During the Second World War, the three Axis powers of Germany, Italy, and Finland mobilized the largest share of their male population. For the Allies, the Soviet Union mobilized the largest share of men, as well as the largest total army of any country, but it was restricted in its ability to mobilize more due to the impact this would have on its economy. Other notable statistics come from the British Empire, where a larger share of men were drafted from Dominions than from the metropole, and there is also a discrepancy between the share of the black and white populations from South Africa.

    However, it should be noted that there were many external factors from the war that influenced these figures. For example, gender ratios among the adult populations of many European countries was already skewed due to previous conflicts of the 20th century (namely WWI and the Russian Revolution), whereas the share of the male population eligible to fight in many Asian and African countries was lower than more demographically developed societies, as high child mortality rates meant that the average age of the population was much lower.

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Marie Kaniecki; Nicole Louise Novak; Sarah Gao; Sioban Harlow; Alexandra Minna Stern (2023). Table_1_Operationalizing racialized exposures in historical research on anti-Asian racism and health: a comparison of two methods.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2023.983434.s001

Table_1_Operationalizing racialized exposures in historical research on anti-Asian racism and health: a comparison of two methods.DOCX

Related Article
Explore at:
docxAvailable download formats
Dataset updated
Jul 6, 2023
Dataset provided by
Frontiers
Authors
Marie Kaniecki; Nicole Louise Novak; Sarah Gao; Sioban Harlow; Alexandra Minna Stern
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

BackgroundAddressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism.MethodsWe used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level.ResultsSurname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup.DiscussionSurname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.

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