Pour réussir le recrutement des membres. L’importance des alliances avec la communauté
Bibliographic record
Abstract
En service social, plusieurs interventions visent les personnes défavorisées et marginalisées généralement perçues comme réfractaires, voire hostiles, aux services sociaux. L’intervention de groupe constitue une méthode de choix pour intervenir auprès de ces personnes. En effet, le groupe offre un cadre favorable au développement des compétences et à l’apprentissage de nouveaux comportements. En outre, la force collective qui émerge d’un groupe contribue à atténuer les sentiments d’impuissance et de désespoir. Cependant, en raison de leur méfiance à l’égard des services, le recrutement des membres représente un défi de taille. Ce texte porte sur l’importance des alliances entre les différents intervenants. Après une brève révision des difficultés que pose le recrutement des personnes opprimées ou marginalisées, l’auteur propose un cadre pour analyser la décision d’accepter de l’aide et fournit quelques exemples de stratégies.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".