Élaboration d'un indice composite de qualité de l'emploi des travailleurs et travailleuses LGBTQ+ du Québec (Canada)
Bibliographic record
Abstract
Résumé L'hétérosexisme et le cisgenrisme peuvent conduire à des expériences d'exclusion sociale vécues au travail, qui nuisent au bien‐être des personnes LGBTQ+. Pour mesurer cette réalité, les auteurs construisent un indice de qualité de l'emploi spécifique, en s'appuyant sur des données issues d'un échantillon de 1 761 travailleurs et travailleuses LGBTQ+ du Québec, recrutés dans le cadre de l'enquête SAVIE‐LGBTQ (2019–2020). Cet indice, créé au moyen de scores factoriels, comprend 16 indicateurs et 5 dimensions. Il possède une cohérence interne acceptable et est associé modérément à la satisfaction au travail des personnes LGBTQ+. L'indice révèle des différences attendues entre les groupes, ce qui soutient sa validité conceptuelle.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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 teacher head, 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".