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Despite a growing body of research on the outcomes of holistic admissions and eliminating standardized test score requirements throughout education, few have documented how organizations transition to holistic review. Implementation, however, may help explain variation in impacts of holistic admissions. This article draws upon theories of organizational routines to examine adoption of holistic review in 13 STEM PhD programs from five universities. We conducted 60- to 90-min interviews with admissions leaders, including a COVID-19 transcript review activity. Data reveal change is multilevel, involving new policy/structural, practice/cultural, and cognitive/interpretive routines, which carry promise for disrupting institutionalized inequities where the politics of changing these routines can be managed. We discuss implications for policy, organizational practice, and future research on academic evaluations.

 

Undergraduate education in the US is racially/ethnically stratified, and there is limited mobility for Black and Latinx BS recipients in STEM majors into the PhD programs from which faculty hiring disproportionately occurs. Bridge programs are proliferating as a means of increasing minoritized students’ enrollment in STEM graduate programs, but little social science examines mechanisms of their impact or how impacts depend on the graduate programs to which students seek access. This sequential mixed methods study of the Cal-Bridge program analyzed trust networks and mechanisms of relational trust as factors in graduate school application, admissions, and enrollment decisions. First, using social network analysis, we examined patterns in the graduate programs to which seven cohorts of Cal-Bridge scholars applied, were admitted, and chose to enroll. Then, we conducted an in-depth case study of the organization in the Cal-Bridge network with the highest centrality: University of California, Irvine’s physics and astronomy PhD program. We find the positive admission and enrollment outcomes at UC Irvine were due to intentional, institutional change at multiple organizational levels. Change efforts complemented the activities of the Cal-Bridge program, creating conditions that cultivated lived experiences of mutual, relational trust between bridge scholars and their faculty advisors and mentors. Findings illustrate mechanisms and antecedents of trust in the transition to graduate education. We use these findings to propose a framework that may inform the design of future research and practical efforts to account for the role of trust in inequities and creating more equitable cultures in STEM. 

Purpose Rising rates of anxiety and depression and the varied costs of these conditions indicate a clear need to create learning environments in which graduate and professional students can more readily thrive. However, the absence of multi-institutional, multi-disciplinary evidence about mental health in graduate education has obscured a clear picture of which populations, contexts and social dynamics merit focused attention and resources. The purpose of this study is therefore to analyze prevalence and risk factors associated with anxiety and depression among a large sample of graduate students, with special attention to how graduate education environments and interactions may be associated with mental health. Design/methodology/approach This paper offers the first multi-institutional, multi-disciplinary analysis of depression and anxiety among US graduate and professional students. Using a sample of 20,888 students randomly sampled within 69 universities, the author compares depression and anxiety prevalence among fields of study with hierarchical cluster modeling. Then, using a conceptual framework that links social support, role strain and self-determination theories, the author estimates fixed effects multivariate logistic regressions to measure how depression and anxiety are associated with experiencing racial discrimination, support from friends and family, perceived competitiveness in one’s classes, and comfort speaking with one’s professors about mental health. Findings Graduate students who endure frequent racial discrimination have odds of screening positive for depression and anxiety that are 2.3 and 3.0 times higher, respectively, than those who never experience discrimination. Support from family and friends moderates these relationships and perceived competitiveness exacerbates them. LGBTQ students and students who self-report that finances are a struggle or tight also have higher odds of depression and anxiety. Students in the humanities, arts and architecture have significantly higher prevalence of depression and anxiety than the sample as a whole. Originality/value The paper offers broadest base of evidence to date about patterns that are usually experienced at the individual level or analyzed institution-by-institution and field-by-field. Specifically, the author identified social dynamics, fields of study and populations where attention to wellbeing may be especially warranted. The conceptual framework and multivariate results clarify how organizational and individual factors in graduate students’ mental health may be intertwined through competitive, discriminatory, or supportive interactions with peers, faculty, family and friends. Findings clarify a need for awareness of the contexts and interactions that graduate students experience as well as individual factors that are associated with student wellbeing. 

We provide statistical measures and additional analyses showing that our original analyses were sound. We use a generalized linear mixed model to account for program-to-program differences with program as a random effect without stratifying with tier and found the GRE-P (Graduate Record Examination physics test) effect is not different from our previous findings, thereby alleviating concern of collider bias. Variance inflation factors for each variable were low, showing that multicollinearity was not a concern. We show that range restriction is not an issue for GRE-P or GRE-V (GRE verbal), and only a minor issue for GRE-Q (GRE quantitative). Last, we use statistical measures of model quality to show that our published models are better than or equivalent to several alternates.