Advancing Diversity in Microbiology: A 55-Year Retrospective Analysis
Bibliographic record
Abstract
Background For over 50 years, affirmative action helped advance equity, diversity and inclusion (EDI) in educational institutions in the United States (U.S.). However, the recent U.S. Supreme Court decision to end affirmative action in college admissions threatens the progress toward EDI. Objective This study aimed to assess the progress in promoting gender and racial diversity within the discipline of microbiology over a 55-year period. We sought to analyze the representation of women and minority groups in faculty ranks, tenure positions, and leadership to identify disparities and trends and determine who will likely be impacted most with the end of affirmative action. Materials and methods This longitudinal retrospective study utilized publicly available and non-identifiable Association of American Medical Colleges (AAMC) data on full-time microbiology faculty from 1967 to 2021. Faculty members were categorized based on academic ranks and tenure status, while gender and racial data were also considered. Results The analysis revealed a consistent dominance of white faculty, with over 60% representation across all academic ranks throughout the study period. The Asian and female faculty representation decreased in senior academic ranks. We observed a positive trend in the annual increase of women in faculty positions, academic ranks, chairs, and tenure positions. Furthermore, Asian faculty demonstrated the most robust surge in representation. However, disparities persisted for black, Hispanic, and Native American faculty members, reflecting broader challenges in their representation. Discussion Although efforts to enhance diversity within microbiology have yielded positive results, underrepresented minority groups still face obstacles in attaining leadership positions and senior academic ranks. The diminishing proportion of women at higher academic ranks raises concerns about potential attrition or lack of promotion opportunities. The end of affirmative action poses a risk of perpetuating this trend, leading to a decline in diversity among microbiology faculty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".