Medical School Deans’ Perceptions of Organizational Climate: Useful Indicators for Advancement of Women Faculty and Evaluation of a Leadership Program’s Impact
Bibliographic record
Abstract
PURPOSE AND METHOD: The authors surveyed U.S. and Canadian medical school deans regarding organizational climate for faculty, policies affecting faculty, processes deans use for developing faculty leadership, and the impact of the Executive Leadership in Academic Medicine (ELAM) Program for Women. RESULTS: The usable response rate was 58% (n = 83/142). Deans perceived gender equity in organizational climate as neutral, improving, or attained on most items and deficient on four. Only three family-friendly policies/benefits were available at more than 68% of medical schools; several policies specifically designed to increase gender equity were available at fewer than 14%. Women deans reported significantly more frequent use than men (P = .032) of practices used to develop faculty leadership. Deans' impressions regarding the impact of ELAM alumnae on their schools was positive (M = 5.62 out of 7), with those having more fellows reporting greater benefit (P = .01). The deans felt the ELAM program had a very positive influence on its alumnae (M = 6.27) and increased their eligibility for promotion (M = 5.7). CONCLUSIONS: This study provides a unique window into the perceptions of medical school deans, important policy leaders at their institutions. Their opinion adds to previous studies of organizational climate focused on faculty perceptions. Deans perceive the organizational climate for women to be improving, but they believe that certain interventions are still needed. Women deans seem more proactive in their use of practices to develop leadership. Finally, deans provide an important third-party judgment for program evaluation of the ELAM leadership intervention, reporting a positive impact on its alumnae and their schools.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".