Bibliographic record
Abstract
Cet article vise d’abord a presenter une cartographie de la situation des femmes « operateurs » dans le secteur de la chimie, de la petrochimie, du raffinage et du gaz (CPRG) au Quebec, secteur toujours hautement masculin, plus de trente ans apres la premiere embauche feminine. Selon le comite sectoriel de la main-d’œuvre (CSMO) CoeffiScience, en 2016, la main-d’œuvre feminine ne represente qu’entre 10 et 15% des employes du secteur. Il apparait important pour la comprehension de ce phenomene social (la difficile mixite) d’investiguer l’histoire et d’analyser son deploiement dans ce secteur pour identifier les actions et les leviers qui permettront d’elaborer des strategies afin de contrer la discrimination systemique et ainsi favoriser l’acces des femmes a des emplois mieux proteges et mieux remuneres. Cependant, la question se pose encore : le milieu est-il pret a travailler de concert ? Car nous emettons l’hypothese qu’une partie de la solution a ce probleme de difficile mixite en emploi passe necessairement par une action collective et /ou concertee.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".