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Using three-level multilevel logistic models with 3rd-, 4th-, and 5th-grade achievement scores and demographics from a 2011–2012 cohort across three states, it tests disparities in identification rates. Results show substantially lower identification likelihood for FRPL, EL, and Black/Latinx students, but 50%–100% of disparities align with early achievement differences rather than identification bias.",{"@graph":69,"@context":114},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/inequality-at-the-starting-line-underrepresentation-in-gifted-identification-and-disparities-in-early-achievement/590201/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/inequality-at-the-starting-line-underrepresentation-in-gifted-identification-and-disparities-in-early-achievement/590201.png","ImageObject",300,407,{"name":92,"@type":93},"Adam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-05","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108],{"name":109,"@type":110,"acceptedAnswer":111},"What explains the disparities in gifted identification rates?","Question",{"text":112,"@type":113},"Between 50% and 100% of gifted identification disparities could be explained by student-level differences in early academic achievement, supporting an opportunity-gap explanation rather than bias alone.","Answer","https://schema.org",{"og:url":83,"og:type":116,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":118,"canonical":83},"index,follow",{"doc_id":120,"site_id":62},590201,1792069061,{"code":4,"msg":5,"data":123},{"doc_id":120,"user_id":124,"nickname":92,"user_avatar":125,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":126,"file_id":127,"file_url":128,"file_type":129,"file_size":130,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":131,"language":132,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":133,"faqs":134,"seo_title":135,"seo_description":67,"update_tm":121,"read_time":136,"preview_page_count":4},1374404737137,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","AERA Open  \nJanuary-December 2023, Vol. 9, No. 1, pp. 1–25 DOI: 10. 1177/23328584231171535  \nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)© The Author(s) 2023. [https://journals.sagepub.com/home/ero](https://journals.sagepub.com/home/ero)  \nInequality at the Starting Line: Underrepresentation in Gifted Identification and Disparities in Early Achievement  \nDaniel A. Long  \nUniversity of Connecticut  \nD. Betsy McCoach  \nUniversity of Connecticut  \nDel Siegle  \nUniversity of Connecticut  \nCarolyn M. Callahan  \nUniversity of Virginia  \nE. Jean Gubbins  \nUniversity of Connecticut  \nIs underrepresentation of Black students, Latinx students, English learners (EL), and students from economically challenging communities in gifted programs due to inequality in early academic achievement or bias in the gifted identification process? Using three-level multilevel logistic models, we examine the degree to which the disparities in gifted identification are due to disparities in early achievement. Our datasets include 3rd-, 4th-, and 5th-grade achievement scores and demographic variables from all students in a 3rd-grade, 2011–2012 cohort across three states. Students who qualified for free/reduced-price lunch (FRPL), EL, and Black or Latinx students were between two to eight times less likely to be identified as gifted compared to non–free/reduced-price lunch, non-EL, and White or Asian students. However, between 50% and 100% of gifted identification disparities could be explained by student-level differences in early academic achievement, which is consistent with an opportunity gap explanation of underrepresentation.  \nKeywords: descriptive analysis, diversity, equity, gifted education, gifted identification, hierarchical linear modeling, regression analyses, underrepresentation  \nFor decades, gifted programs have identified students from White, Asian, and upper-income families at notably higher rates than students who are low-income, English learners (EL), Black, and Latinx (Peters et al., 2019; U.S. Department of Education (USDOE), 2016; Worrell & Dixson, 2020; Yoon & Gentry, 2009) . The 2018 Office of Civil Rights (OCR) data indicated that nationally, among elementary schools with gifted education programs, 9% of White students were identified as gifted compared to 5% of Black and 5% of Latinx students.1 Black or Latinx students were only 55% as likely to be identified as gifted compared to White students (i.e. , Black/White and Latinx/ White relative risks of . 55) .2  \nMost of the research on underrepresentation focuses on raw disparities in disproportionality (Peters et al., 2019) . Many observers of gifted identification interpret this raw disproportionality as evidence of bias in the gifted identification process (Ford, 2010; USDOE, 2016; Yaluma & Tyner, 2021) . However, the cause of such disproportionality is unclear: raw disproportionality might not be evidence of bias in the identification process but could instead result from student differences that exist at the beginning of the identification process (Plucker & Peters, 2016, 2018; Simonsen et al., 2020; Worrell & Dixson, 2020, 2022) .  \nTo distinguish between differences due to bias in identification processes and disparities due to early achievement  \nCreative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons  \nAttribution-NonCommercial 4.0 License ([https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)) which permits non-commercial use,  \nreproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ([https://us.sagepub.com/en-us/nam/open-access-at-sage](https://us.sagepub.com/en-us/nam/open-access-at-sage)).  \nLong et al.  \ndifferences, we examine whether disproportionality exists after controlling for s","cbCaitcAxm14nEAI","https://ap.wps.com/l/cbCaitcAxm14nEAI","pdf",1939840,25,"English","# Introduction\n## Research Question and Approach\n## Background on Underrepresentation and Disproportionality\n# Literature Review\n## Three Explanatory Factors in Gifted Identification\n## Bias in Identification Processes","[{\"question\":\"What explains the disparities in gifted identification rates?\",\"answer\":\"Between 50% and 100% of gifted identification disparities could be explained by student-level differences in early academic achievement, supporting an opportunity-gap explanation rather than bias alone.\"}]","Inequality at the Starting Line: Underrepresentation in Gifted Identification and Disparities in Early Achievement | PDF",63]