La théorie des ressources communes : cadre interprétatif pour les institutions publiques ?
Bibliographic record
Abstract
Les systèmes sociaux complexes étudiés par Elinor Ostrom et les chercheurs associés caractérisent souvent des réseaux de petite ou de moyenne échelle, tant pour des ressources matérielles qu’informationnelles. Mais d’un point de vue citoyen, les outils, institutions des collectifs sociopolitiques (appelés école, voirie publique, hôpitaux, universités , etc.) peuvent-ils être pensés sous l’angle des ressources communes et, à ce titre, donner lieu à l’émergence d’une gouvernance participative, en étant vus comme à préserver par les concernés ? Pour favoriser une telle lecture, il nous faut clarifier quelques apports de l’école d’Ostrom, amorcer une analyse sociale des composantes d’une gouvernance des communs fondée sur la participation et identifier certaines questions à creuser ultérieurement, notamment les problèmes posés dans le cadre d’une économie largement financiarisée et abstraite des besoins matériels les plus immédiats.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".