Individual

Abstract

Objective: Perceptions of agency and communality vary by race and gender, which may be contributing to the persistent gender and racial inequality in radiology. The objective of this study was to determine if there are differences in the use of agentic and communal language in letters of recommendation for radiology residency programs based on the demographics of the applicant and letter writer.

Abstract

Background: While program director (PD) letters of recommendation (LOR) are subject to bias, especially against those underrepresented in medicine, these letters are one of the most important factors in fellowship selection. Bias manifests in LOR in a number of ways, including biased use of agentic and communal terms, doubt raising language, and description of career trajectory. To reduce bias, specialty organizations have recommended standardized PD LOR.

ABSTRACT

Dropping the GRE is just a first step toward holistic admissions. To further reduce bias in applicant evaluations, the UMass-Amherst geosciences program has changed the way it assesses students.

Abstract: Physics departments are increasingly working to improve diversity in graduate programs by using more holistic strategies in their admission and retention practices. However, completion rates for traditionally underserved groups are still problematic. By understanding and accounting for faculty and student divergence on challenges faced in retention, graduate programs will be better equipped to enact change.

"Earth and environmental sciences have some of the least diverse racial and ethnic representation in academia. To face profound future challenges, the fields need to address the inequities of the past and how they inform the present."

Abstract: Demographics of the science, technology, engineering, and mathematics (STEM) workforce and student body in the US and Europe continue to show severe underrepresentation of Black, Indigenous, and people of color (BIPOC). Among the documented causes of the persistent lack of diversity in STEM are bias, discrimination, and harassment of members of underrepresented minority groups (URMs). These issues persist due to continued marginalization, power imbalances, and lack of adequate policies against misconduct in academic and other scientific institutions.