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Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019
We aimed to investigate whether implicit linguistic biases exist in letters of recommendation (LORs) for applicants to radiation oncology (RO) residency. LORs (n = 487) written for applicants (n = 125) invited to interview at a single RO residency program from the 2015 to 2019 application cycles wer...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591242/ https://www.ncbi.nlm.nih.gov/pubmed/33111188 http://dx.doi.org/10.1007/s13187-020-01907-x |
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author | Chapman, Bhavana V. Rooney, Michael K. Ludmir, Ethan B. De La Cruz, Denise Salcedo, Abigail Pinnix, Chelsea C. Das, Prajnan Jagsi, Reshma Thomas, Charles R. Holliday, Emma B. |
author_facet | Chapman, Bhavana V. Rooney, Michael K. Ludmir, Ethan B. De La Cruz, Denise Salcedo, Abigail Pinnix, Chelsea C. Das, Prajnan Jagsi, Reshma Thomas, Charles R. Holliday, Emma B. |
author_sort | Chapman, Bhavana V. |
collection | PubMed |
description | We aimed to investigate whether implicit linguistic biases exist in letters of recommendation (LORs) for applicants to radiation oncology (RO) residency. LORs (n = 487) written for applicants (n = 125) invited to interview at a single RO residency program from the 2015 to 2019 application cycles were included for analysis. Linguistic Inquiry and Word Count (LIWC) software was used to evaluate LORs for length and a dictionary of predetermined themes. Language was evaluated for gender bias using a publicly available gender bias calculator. Non-parametric tests were used to compare linguistic domain scores. The median number of the LORs per applicant was 4 (range 3–5). No significant differences by applicant gender were detected in LIWC score domains or gender bias calculator (P > 0.05). However, LORs for applicants from racial/ethnic backgrounds underrepresented in medicine were less likely to include standout descriptors (P = 0.008). Male writers were less likely to describe applicant characteristics related to patient care (P < 0.0001) and agentic personality (P = 0.006). LORs written by RO were shorter (P < 0.0001) and included fewer standout descriptors (P = 0.014) but were also more likely to include statements regarding applicant desirability (P = 0.045) and research (P = 0.008). While language was globally male-biased, assistant professors were less likely than associate professors (P = 0.0064) and full professors (P = 0.023) to use male-biased language. Significant linguistic differences were observed in RO residency LORs, suggesting that implicit biases related to both applicants and letter writers may exist. Recognition, and ideally eradication, of such biases are crucial for fair and equitable evaluation of a diverse applicant pool of RO residency candidates. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version contains supplementary material available at 10.1007/s13187-020-01907-x. |
format | Online Article Text |
id | pubmed-7591242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-75912422020-10-28 Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 Chapman, Bhavana V. Rooney, Michael K. Ludmir, Ethan B. De La Cruz, Denise Salcedo, Abigail Pinnix, Chelsea C. Das, Prajnan Jagsi, Reshma Thomas, Charles R. Holliday, Emma B. J Cancer Educ Article We aimed to investigate whether implicit linguistic biases exist in letters of recommendation (LORs) for applicants to radiation oncology (RO) residency. LORs (n = 487) written for applicants (n = 125) invited to interview at a single RO residency program from the 2015 to 2019 application cycles were included for analysis. Linguistic Inquiry and Word Count (LIWC) software was used to evaluate LORs for length and a dictionary of predetermined themes. Language was evaluated for gender bias using a publicly available gender bias calculator. Non-parametric tests were used to compare linguistic domain scores. The median number of the LORs per applicant was 4 (range 3–5). No significant differences by applicant gender were detected in LIWC score domains or gender bias calculator (P > 0.05). However, LORs for applicants from racial/ethnic backgrounds underrepresented in medicine were less likely to include standout descriptors (P = 0.008). Male writers were less likely to describe applicant characteristics related to patient care (P < 0.0001) and agentic personality (P = 0.006). LORs written by RO were shorter (P < 0.0001) and included fewer standout descriptors (P = 0.014) but were also more likely to include statements regarding applicant desirability (P = 0.045) and research (P = 0.008). While language was globally male-biased, assistant professors were less likely than associate professors (P = 0.0064) and full professors (P = 0.023) to use male-biased language. Significant linguistic differences were observed in RO residency LORs, suggesting that implicit biases related to both applicants and letter writers may exist. Recognition, and ideally eradication, of such biases are crucial for fair and equitable evaluation of a diverse applicant pool of RO residency candidates. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version contains supplementary material available at 10.1007/s13187-020-01907-x. Springer US 2020-10-27 2022 /pmc/articles/PMC7591242/ /pubmed/33111188 http://dx.doi.org/10.1007/s13187-020-01907-x Text en © American Association for Cancer Education 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chapman, Bhavana V. Rooney, Michael K. Ludmir, Ethan B. De La Cruz, Denise Salcedo, Abigail Pinnix, Chelsea C. Das, Prajnan Jagsi, Reshma Thomas, Charles R. Holliday, Emma B. Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title | Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title_full | Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title_fullStr | Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title_full_unstemmed | Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title_short | Linguistic Biases in Letters of Recommendation for Radiation Oncology Residency Applicants from 2015 to 2019 |
title_sort | linguistic biases in letters of recommendation for radiation oncology residency applicants from 2015 to 2019 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591242/ https://www.ncbi.nlm.nih.gov/pubmed/33111188 http://dx.doi.org/10.1007/s13187-020-01907-x |
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