MétaCan
Menu
Back to cohort
Record W2980022814 · doi:10.1016/j.apergo.2019.102960

Impacts of considering sex and gender during intervention studies in occupational health: Researchers’ perspectives

2019· article· en· W2980022814 on OpenAlexafffund
Marie Laberge, Vanessa Blanchette-Luong, Arnaud Blanchard, Hélène Sultan‐Taïeb, Jessica Riel, Valérie Lederer, Johanne Saint-Charles, Céline Chatigny, Mélanie Lefrançois, Jena Webb, Marie-Ève Major, Cathy Vaillancourt, Karen Messing

Bibliographic record

VenueApplied Ergonomics · 2019
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsInstitut National de la Recherche ScientifiqueArmand Frappier MuseumUniversité du Québec en OutaouaisCentre Hospitalier de l’Université de MontréalUniversité de MontréalUniversité de SherbrookeCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à Montréal
FundersInstitute of Gender and HealthSocial Sciences and Humanities Research Council of Canada
KeywordsThematic analysisPsychological interventionIntervention (counseling)Occupational safety and healthHuman factors and ergonomicsApplied psychologyPsychologyContent analysisGender analysisPoison controlQualitative researchMedicineEnvironmental healthPolitical scienceSociologyNursingSocial science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.279
metaresearch head score (Gemma)0.336
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2790.336
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0070.006
Open science0.0030.005
Research integrity0.0040.005
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 head0.173
GPT teacher head0.468
Teacher spread0.295 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations35
Published2019
Admission routes2
Has abstractno

Explore more

Same venueApplied ErgonomicsSame topicWorkplace Health and Well-beingFrench-language works237,207