Porter plainte pour harcèlement psychologique au travail
Bibliographic record
Abstract
Cet article brosse un portrait des plaintes écrites déposées à la Commission des normes du travail du Québec entre le 1erjuin 2004 et le 30 avril 2005. Au total, 236 plaintes de harcèlement psychologique au travail ont constitué le corpus d’analyse. Les principaux résultats montrent que parmi l’ensemble des cas analysés, 63 % des plaignants sont des femmes. Près de 95 % des plaignants ont avancé avoir subi du harcèlement à caractère répétitif. Les cinq premiers motifs de plainte sont les propos et les gestes vexatoires, les atteintes aux conditions de travail, la menace de congédiement, la mise en échec de la personne et l’isolement. Par ailleurs, ce sont généralement les gestionnaires qui sont désignés comme personnes mises en cause. À la lumière de ces résultats, il est important que les organisations se dotent de systèmes de veille pour détecter les cas et d’outils de gestion pour désamorcer les situations qui comportent un potentiel de harcèlement psychologique.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
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".