La proximité épistémique comme concept clé pour penser la notion d’allié.e dans les recherches en travail social auprès des groupes marginalisés
Bibliographic record
Abstract
Malgré de bonnes intentions, certain.e.s chercheur.euse.s reproduisent des oppressions envers les groupes marginalisés dans leurs recherches. Cet article s’intéresse spécifiquement au développement de pratiques d’allié.e dans les recherches en travail social afin d’éviter la reconduction d’oppressions. Mobilisant les théories des injustices épistémiques comme cadre théorique, cet article suggère de fonder les pratiques d’allié.e sur le concept de proximité épistémique. Après une recension critique des écrits sur les concepts d’allié.e et de proximité, cet article offre une redéfinition du concept de proximité épistémique, développé en géographie et en économie, à la lumière des théories des injustices épistémiques. Il propose enfin quelques recommandations pour des pratiques d’allié.e.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.044 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".