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Differential retention contributes to racial/ethnic disparity in U.S. academia

Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated d...

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Autores principales: Shaw, Allison K., Accolla, Chiara, Chacón, Jeremy M., Mueller, Taryn L., Vaugeois, Maxime, Yang, Ya, Sekar, Nitin, Stanton, Daniel E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635368/
https://www.ncbi.nlm.nih.gov/pubmed/34851964
http://dx.doi.org/10.1371/journal.pone.0259710
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author Shaw, Allison K.
Accolla, Chiara
Chacón, Jeremy M.
Mueller, Taryn L.
Vaugeois, Maxime
Yang, Ya
Sekar, Nitin
Stanton, Daniel E.
author_facet Shaw, Allison K.
Accolla, Chiara
Chacón, Jeremy M.
Mueller, Taryn L.
Vaugeois, Maxime
Yang, Ya
Sekar, Nitin
Stanton, Daniel E.
author_sort Shaw, Allison K.
collection PubMed
description Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world’s largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios.
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spelling pubmed-86353682021-12-02 Differential retention contributes to racial/ethnic disparity in U.S. academia Shaw, Allison K. Accolla, Chiara Chacón, Jeremy M. Mueller, Taryn L. Vaugeois, Maxime Yang, Ya Sekar, Nitin Stanton, Daniel E. PLoS One Research Article Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world’s largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios. Public Library of Science 2021-12-01 /pmc/articles/PMC8635368/ /pubmed/34851964 http://dx.doi.org/10.1371/journal.pone.0259710 Text en © 2021 Shaw et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shaw, Allison K.
Accolla, Chiara
Chacón, Jeremy M.
Mueller, Taryn L.
Vaugeois, Maxime
Yang, Ya
Sekar, Nitin
Stanton, Daniel E.
Differential retention contributes to racial/ethnic disparity in U.S. academia
title Differential retention contributes to racial/ethnic disparity in U.S. academia
title_full Differential retention contributes to racial/ethnic disparity in U.S. academia
title_fullStr Differential retention contributes to racial/ethnic disparity in U.S. academia
title_full_unstemmed Differential retention contributes to racial/ethnic disparity in U.S. academia
title_short Differential retention contributes to racial/ethnic disparity in U.S. academia
title_sort differential retention contributes to racial/ethnic disparity in u.s. academia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635368/
https://www.ncbi.nlm.nih.gov/pubmed/34851964
http://dx.doi.org/10.1371/journal.pone.0259710
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