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Record W2422046213 · doi:10.1097/acm.0000000000001281

Women in Academic Medicine Leadership: Has Anything Changed in 25 Years?

2016· article· en· W2422046213 on OpenAlexaffabout
Paula A. Rochon, Frank Davidoff, Wendy Levinson

Bibliographic record

VenueAcademic Medicine · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of TorontoWomen's College Hospital
Fundersnot available
KeywordsAcademic medicinePromotion (chess)Affect (linguistics)Face (sociological concept)Medical educationPsychologyPublic relationsPolitical scienceMedicineSociologySocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Over the past 25 years, the number of women graduating from medical schools in the United States and Canada has increased dramatically to the point where roughly equal numbers of men and women are graduating each year. Despite this growth, women continue to face challenges in moving into academic leadership positions. In this Commentary, the authors share lessons learned from their own careers relevant to women's careers in academic medicine, including aspects of leadership, recruitment, editorship, promotion, and work-life balance. They provide brief synopses of current literature on the personal and social forces that affect women's participation in academic leadership roles. They are persuaded that a deeper understanding of these realities can help create an environment in academic medicine that is generally more supportive of women's participation, and that specifically encourages women in medicine to take on academic leadership positions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.013
Scholarly communication0.0100.008
Open science0.0020.003
Research integrity0.0140.018
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.237
GPT teacher head0.359
Teacher spread0.122 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainIncentives
GenreEmpirical

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".

Quick stats

Citations164
Published2016
Admission routes2
Has abstractyes

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