Dev K. Dalal, Jason G. Randall, Ho Kwan Cheung, Brandon Gorman, Sylvia G. Roch, K. Williams
{"title":"标准化考试的替代方案是否存在偏见?对推荐信的调查","authors":"Dev K. Dalal, Jason G. Randall, Ho Kwan Cheung, Brandon Gorman, Sylvia G. Roch, K. Williams","doi":"10.1080/15305058.2021.2019751","DOIUrl":null,"url":null,"abstract":"Abstract Individuals concerned with subgroup differences on standardized tests suggest replacing these tests with holistic evaluations of unstructured application materials, such as letters of recommendation (LORs), which they posit show less bias. We empirically investigate this proposition that LORs are bias-free, and argue that LORs might actually invite systematic, race and gender subgroup differences in the content and evaluation of LORs. We text analyzed over 37,000 LORs submitted on behalf of over 10,000 graduate school applicants. Results showed that LOR content does differ across applicants. Furthermore, we see some systematic gender, race, and gender-race intersection differences in LOR content. Content of LORs also systematically differed between degree programs (S.T.E.M. vs. non-S.T.E.M.) and degree sought (doctoral vs. masters). Finally, LOR content alone did not predict an appreciable amount of variance in offers of admission (the first barrier to increasing diversity and inclusion in graduate programs). Our results, combined with past research on LOR content bias, highlight concerns that LORs can be biased against marginalized groups. We conclude with suggestions for reducing potential bias in LOR and for increasing diversity in graduate programs.","PeriodicalId":46615,"journal":{"name":"International Journal of Testing","volume":"22 1","pages":"21 - 42"},"PeriodicalIF":1.0000,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Is there bias in alternatives to standardized tests? An investigation into letters of recommendation\",\"authors\":\"Dev K. Dalal, Jason G. Randall, Ho Kwan Cheung, Brandon Gorman, Sylvia G. Roch, K. Williams\",\"doi\":\"10.1080/15305058.2021.2019751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Individuals concerned with subgroup differences on standardized tests suggest replacing these tests with holistic evaluations of unstructured application materials, such as letters of recommendation (LORs), which they posit show less bias. We empirically investigate this proposition that LORs are bias-free, and argue that LORs might actually invite systematic, race and gender subgroup differences in the content and evaluation of LORs. We text analyzed over 37,000 LORs submitted on behalf of over 10,000 graduate school applicants. Results showed that LOR content does differ across applicants. Furthermore, we see some systematic gender, race, and gender-race intersection differences in LOR content. Content of LORs also systematically differed between degree programs (S.T.E.M. vs. non-S.T.E.M.) and degree sought (doctoral vs. masters). Finally, LOR content alone did not predict an appreciable amount of variance in offers of admission (the first barrier to increasing diversity and inclusion in graduate programs). Our results, combined with past research on LOR content bias, highlight concerns that LORs can be biased against marginalized groups. We conclude with suggestions for reducing potential bias in LOR and for increasing diversity in graduate programs.\",\"PeriodicalId\":46615,\"journal\":{\"name\":\"International Journal of Testing\",\"volume\":\"22 1\",\"pages\":\"21 - 42\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Testing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/15305058.2021.2019751\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Testing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15305058.2021.2019751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Is there bias in alternatives to standardized tests? An investigation into letters of recommendation
Abstract Individuals concerned with subgroup differences on standardized tests suggest replacing these tests with holistic evaluations of unstructured application materials, such as letters of recommendation (LORs), which they posit show less bias. We empirically investigate this proposition that LORs are bias-free, and argue that LORs might actually invite systematic, race and gender subgroup differences in the content and evaluation of LORs. We text analyzed over 37,000 LORs submitted on behalf of over 10,000 graduate school applicants. Results showed that LOR content does differ across applicants. Furthermore, we see some systematic gender, race, and gender-race intersection differences in LOR content. Content of LORs also systematically differed between degree programs (S.T.E.M. vs. non-S.T.E.M.) and degree sought (doctoral vs. masters). Finally, LOR content alone did not predict an appreciable amount of variance in offers of admission (the first barrier to increasing diversity and inclusion in graduate programs). Our results, combined with past research on LOR content bias, highlight concerns that LORs can be biased against marginalized groups. We conclude with suggestions for reducing potential bias in LOR and for increasing diversity in graduate programs.