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Record W2921381402 · doi:10.1186/s12916-018-1246-9

Challenges and opportunities in examining and addressing intersectional stigma and health

2019· letter· en· W2921381402 on OpenAlexafffund
Janet M. Turan, Melissa A. Elafros, Carmen H. Logie, Swagata Banik, Bülent Turan, Kaylee B. Crockett, Bernice A. Pescosolido, Sarah M. Murray

Bibliographic record

VenueBMC Medicine · 2019
Typeletter
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsWomen's College Hospital
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institute on Drug AbuseFogarty International CenterNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingCanadian Institutes of Health ResearchCenter for AIDS Research, University of Alabama at BirminghamIndian Council of Medical ResearchCanada Research ChairsNational Institutes of HealthAgency for Healthcare Research and QualityCenter for AIDS Research, University of WashingtonNational Cancer InstituteUniversity of Toronto
KeywordsMedicineStigma (botany)Health equitySocial stigmaMEDLINEPsychiatryPublic healthNursingFamily medicineHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.218
metaresearch head score (Gemma)0.180
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.218
Threshold uncertainty score0.965

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2180.180
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0070.008
Science and technology studies0.0150.041
Scholarly communication0.0180.031
Open science0.0060.024
Research integrity0.0080.016
Insufficient payload (model declined to judge)0.0070.001

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 head0.569
GPT teacher head0.436
Teacher spread0.133 · 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 designNot applicable
Domainnot available
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

Citations744
Published2019
Admission routes2
Has abstractyes

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