Pour une pratique inclusive de la diversité en travail social de groupe : repères théoriques et méthodologiques
Bibliographic record
Abstract
La question de la diversité suscite de plus en plus d’intérêt dans les écrits en travail social de groupe et elle est abordée principalement soit selon des modèles théoriques particuliers soit selon la composition du groupe et ses effets sur le processus. Après le rappel de repères théoriques pour définir et conceptualiser la diversité, cet article présente les principes d’intervention associés à une pratique inclusive de la diversité. Il conclut en explorant les limites du concept, tout en mettant en relief ses potentialités.The issue of diversity is increasingly discussed within the literature on social work with groups, in particular in relation to specific theoretical models and to group composition. This article situates diversity and presents some guidelines for an inclusive groupwork practice. It discusses how diversity is defined and conceptualized, highlighting its limits and its potential.
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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 | 0.086 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.056 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".