L’acceptabilité sociale : une notion en consolidation
Bibliographic record
Abstract
Cet article examine un enjeu particulièrement important pour toutes les entreprises qui ont des ancrages locaux marqués : l’acceptabilité sociale. Cette notion s’est imposé au cours des dernières années dans différents contextes à la suite de controverses entre entreprises et communautés locales. Cependant, sa diffusion parmi les praticiens et les décideurs contraste avec sa conceptualisation limitée en tant qu’objet de recherche. Les apports de cet article sont de deux ordres. Le premier est théorique et vise à cartographier les définitions de l’acceptabilité sociale, cerner ses enjeux et proposer un modèle multi-niveaux de l’acceptabilité sociale. Le deuxième apport est empirique. L’étude en profondeur des niveaux d’acceptabilité sociale à partir de l’analyse de l’évolution des relations entre Hydro-Québec et la nation crie sur près de quatre décennies (1971-2012) illustre ces enjeux et l’évolution de leur gestion.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Conceptual mapping of the notion of social acceptability in management; the object is a business/social concept, not research practice.
It studies social acceptability and Hydro-Québec relations, not the Canadian research system.
Conceptualizes social acceptability of firms and communities; management/STS of industry, not of research.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.068 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".