Entrevue guidée avec Colette Dion Hubert
Bibliographic record
Abstract
Collette Dion-Hubert est une pionnière dans le domaine de l’ergothérapie et de l’utilisation de l’ergonomie de l’activité de travail en réadaptation au Québec. Selon elle, alors que l’ergothérapie procède d’une approche individuelle des problématiques, l’ergonomie apporte une vision plus globale qui est essentielle à la transformation des situations de travail pathogènes. Elle a comme espoir que les pénuries de main-d’œuvre qui se dessinent dans certains métiers créeront de nouvelles possibilités d’insertion sécuritaire des « personnes différentes » au travail. Collette Dion-Hubert is a pioneer in the field of occupational therapy and the use of ergonomics of the work activity in rehabilitation in Québec. According to her, while occupational therapy stems from an individual approach to the problems, ergonomics provides a more comprehensive view that is vital in the transformation of pathogenic work situations. Her hope is that the labour shortages that are occurring in some professions will create new possibilities for the safe integration of « different people » into the work. Colette Dion-Hubert es una pionera en el campo de la ergoterapia y de la utilización de la ergonomía de la actividad en readaptación, en Quebec. Según ella, mientras la ergoterapia enfoca los problemas de una manera individual, la ergonomía aporta una visión más global, esencial cuando se trata de transformar situaciones de trabajo patógenas. Colette Dion-Hubert tiene la esperanza que la penuria de mano de obra que se prevee en varios oficios, creará nuevas posibilidades para la inserción de « personas diferentes » a trabajos que respeten su seguridad.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.030 |
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".