La gestion des bénévoles dans les organismes à but non lucratif : une approche différenciée
Bibliographic record
Abstract
Les bénévoles sont reconnus comme étant une composante essentielle des organismes à but non lucratif (OBNL). Plusieurs auteurs s’accordent par ailleurs à reconnaître qu’ils constituent l’un des traits caractéristiques des organisations du tiers secteur (Keyton, Wilson et Geiger, 1990; Wymer, 2003; Brudney, 2005; McCurley, 2005). Parallèlement à son importance sur le plan organisationnel, le recours aux bénévoles s’affirme comme une tendance lourde de l’économie nationale (Statistique Canada, 2012). À partir des résultats d’une recherche empirique, cet article propose une typologie originale des bénévoles qui implique, en ce qui concerne ces derniers, une approche de gestion différenciée qui tient compte des attentes et des motivations spécifiques de chaque catégorie.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".