Des accords aux leviers d’émancipation : pour une lecture critique des ententes sur les répercussions et les avantages (ERA)
Bibliographic record
Abstract
Cet article examine la performativité et les limites des ententes sur les répercussions et les avantages (ERA) en tant qu’outils de responsabilité sociétale pour l’industrie minière et leviers potentiels d’autodétermination pour les communautés autochtones. Ces accords, investis comme des espaces de dialogue stratégique, permettent aux communautés, détentrices de droits distincts, de réaffirmer leur autorité territoriale et de négocier des mécanismes de contrôle dans un cadre structuré par des dynamiques de pouvoir héritées du colonialisme. À partir d’une analyse d’une ERA conclue en 2014 entre une communauté crie d’Eeyou Istchee et une jeune entreprise d’extraction du spodumène, cette étude examine les tensions et limites inhérentes à ces dispositifs contractuels. Cette analyse remet en question les conditions de réappropriation des ERA afin d’en faire de véritables leviers d’émancipation et de transformation des rapports de pouvoir dans l’industrie minière.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".