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Record W4394762531 · doi:10.1136/fmch-2024-002828

Storylines of family medicine X: standing up for diversity, equity and inclusion

2024· article· en· W4394762531 on OpenAlexaff
William Ventres, Leslie A Stone, Wayne W Bryant, Mario Pacheco, Edgar Figueroa, Francis N Chu, Shailendra Prasad, David Blane, Na’amah Razon, Ranit Mishori, Robert L. Ferrer, Garrett Kneese

Bibliographic record

VenueFamily Medicine and Community Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsEquity (law)Diversity (politics)WorkforceInclusion (mineral)Health careHealth equityMedical homeFamily medicineMedicineSociologyPublic relationsPsychologyPolitical scienceGender studiesPrimary careLaw

Abstract

fetched live from OpenAlex

Storylines of Family Medicineis a 12-part series of thematically linked mini-essays with accompanying illustrations that explore the many dimensions of family medicine as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In ‘X: standing up for diversity, equity and inclusion’, authors address the following themes: ‘The power of diversity—why inclusivity is essential to equity in healthcare’, ‘Medical education for whom?’, ‘Growing a diverse and inclusive workforce’, ‘Therapeutic judo—an inclusive approach to patient care’, ‘Global family medicine—seeing the world “upside down”’, ‘The inverse care law‘, ‘Social determinants of health as a lens for care’, ‘Why family physicians should care about human rights’ and ‘Toward health equity—theopportunome’.May the essays that follow inspire readers to promote change.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.012
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0080.001

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 head0.400
GPT teacher head0.548
Teacher spread0.148 · 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 designQualitative
Domainnot available
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

Citations2
Published2024
Admission routes1
Has abstractyes

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