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Record W4212893373 · doi:10.7759/cureus.22535

Sticky Floor, Broken Ladder, and Glass Ceiling in Academic Obstetrics and Gynecology in the United States and Canada

2022· article· en· W4212893373 on OpenAlexaffabout
Katherine Y Kim, Emily L Kearsley, Hsin Yun Yang, John P. Walsh, Mehr Jain, Laura Hopkins, Ahmad B Wazzan, Faisal Khosa

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsVancouver General HospitalUniversity of SaskatchewanMcMaster UniversityQueen's University
Fundersnot available
KeywordsObstetrics and gynaecologyMedicineScopusGlass ceilingFamily medicineChristian ministryDemographyMEDLINEPregnancyPolitical science

Abstract

fetched live from OpenAlex

. College Station, TX: StataCorp LP). Results Among 3556 American and 689 Canadian Obstetrics and Gynaecology physicians, women comprised 60.9% and 61.4%, respectively. Among physicians with professorships, women physicians comprised 36.2% and 35.8% in the United States and Canada, respectively. When examining the gender proportion of physicians in leadership roles, women comprised 52.2% and 56.1% in the United States and Canada, respectively. The h-index between men and women physicians showed a significant difference overall in both the United States (p<0.001) and Canada (p<0.001), indicating that men have higher academic output. Conclusion Although the overall proportion of women academic staff physicians in Obstetrics and Gynaecology is higher than the proportion of men, there are more men who had a full professor rank. Men also had higher academic productivity.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.028
GPT teacher head0.275
Teacher spread0.248 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

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