Quelle recherche-action participative au service de la democratie participative a Railcoop ? Retour sur une experimentation
Bibliographic record
Abstract
Si savoir, c’est pouvoir, alors la démocratisation des méthodes de recherche pourrait se traduire par un renforcement du pouvoir d’agir des membres dans leurs organisations. Dans les Sociétés Coopératives d’Intérêt Collectif (SCIC) qui associent plusieurs parties prenantes dans leur gouvernance, c’est un défi au cœur du processus de production. Cet article propose d’explorer ce rapport entre démocratie participative et recherche-action participative (RAP) dans une coopérative à partir d’une expérimentation menée par des sociétaires (dont une chercheuse et un chercheur, qui ont écrit ce présent article), au sein de la SCIC ferroviaire Railcoop. Parmi ses 14 000 sociétaires, environ 800 sont impliqués dans 30 cercles de sociétaires. Cette étude de cas met en lumière les apports et les limites d’une RAP pour nourrir la démocratie participative d’une coopérative.
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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 | 0.059 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".