A Bottom-up Definition of Social Acceptability: Territorial Dynamics Related to Wind Energy Projects in Quebec (Canada)
Bibliographic record
Abstract
In Quebec a number of energy projects face local opposition. Social acceptability is increasingly put forward by private or public authorities as an answer to these conflicts. The notion is still vague, however, and open to diverse interpretations. In this article, we propose a definition and an analysis grid in which social acceptability is considered as part of a territorialization process of major energy projects that needs to fit in with other local projects. The structuring of such a process would need to be considered at three different levels: a political assessment process of a sociotechnical project (micro level) where plural actors, engaged at several scales, interact and negotiate agreements. These are then (meso level) institutionalized through rules considered as legitimate since they are coherent with the vision which the concerned actors have of their territory and the development model they have chosen (macro). The social dynamics observed regarding wind energy siting in an eastern region of Quebec, namely Gaspesie, serves to illustrate this proposition. To conclude, we discuss the limits and resistances to the adoption of such a definition of social acceptability which privileges bottom up territorial dynamics that reveal the dynamic, plural, and sometimes conflictual, composition of local communities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".