Identité professionnelle en travail social : atteindre l’équilibre dans un contexte déséquilibrant
Bibliographic record
Abstract
Le travail social s’exerce aujourd’hui dans un contexte de plus en plus règlementé. Ce contexte pose l’exigence aux travailleuses sociales de se positionner entre les demandes organisationnelles et leurs valeurs professionnelles. Ceci peut avoir un impact sur leur identité professionnelle.Dans cet article, nous résumons les résultats de deux projets de recherche sur l’identité professionnelle en travail social au Québec et identifions un thème commun: le désir d’atteindre un équilibre dans des contextes de plus en plus technicisants et normalisants. Nous concluons en proposant un retour à l’éthique des vertus afin de favoriser une pratique éthique ancrée dans une identité professionnelle forte.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".