MétaCan
Menu
Back to cohort
Record W2898972671 · doi:10.1016/s0140-6736(18)32268-2

Differences in clinical practice guideline authorship by gender

2018· letter· en· W2898972671 on OpenAlexaff
Erica Merman, Daniel Pincus, Conor Bell, Nicola Goldberg, Simina Luca, Marnie Jakab, Karen E. A. Burns, Sharon E. Straus, Sangeeta Mehta

Bibliographic record

VenueThe Lancet · 2018
Typeletter
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsMount Sinai HospitalSt. Michael's HospitalUniversity Health NetworkQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsGuidelineScopusFamily medicineMedicineMEDLINEClinical PracticeGender diversityPsychologyPathologyPolitical science

Abstract

fetched live from OpenAlex

Clinical practice guidelines (CPGs) are systematically developed statements designed to guide clinical decision making for patient populations around the world. The content of CPGs should reflect international diversity, as should the authors who write them.1 Although studies have evaluated gender representation of authors of original medical research,2,3 the gender of CPG authors has not been studied. We sought to evaluate the representation of female physician authors, and of female authors overall, in CPGs.

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)0.127
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.989
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.127
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0220.014
Insufficient payload (model declined to judge)0.0130.003

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 head0.236
GPT teacher head0.433
Teacher spread0.197 · 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
GenreCommentary

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

Citations63
Published2018
Admission routes1
Has abstractno

Explore more

Same venueThe LancetSame topicDiversity and Career in MedicineFrench-language works237,207