Caractéristiques des médecins prescrivant des psychotropes davantage aux femmes qu’aux hommes
Bibliographic record
Abstract
Les différences observées dans l'état de santé et l'utilisation des services médicaux, selon le sexe, se sont avérées insuffisantes pour expliquer une plus grande consommation de psychotropes chez les femmes que chez les hommes dans les pays industrialisés. Nous avons testé l'hypothèse selon laquelle les habitudes de prescription des médecins expliquent une partie importante de cette observation. Nous démontrons, à l'aide des données de la Régie de l'assurance-maladie du Québec pour les personnes âgées de 65 ans et plus, que le profil socio-démographique et le style de gestion des médecins prescripteurs sont associés de façon significative au pourcentage d'hommes et de femmes ayant obtenu une ordonnance de psychotrope dans leurs pratiques.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".