What scope for statistics on the social economy at the international level?
Bibliographic record
Abstract
Bien que partageant un socle commun, le périmètre statistique de l’économie sociale (ES) varie d’un pays à l’autre. Dans de nombreux pays, l’ES demeure entièrement sous le radar des agences statistiques. Ceci reflète le déploiement historique et progressif de l’ES dans différents contextes nationaux. Des guides ont été développés pour promouvoir et harmoniser les statistiques de différents sous-ensembles de l’ES à l’échelle internationale. Récemment, l’un de ces guides a proposé de couvrir l’ensemble. Il en a toutefois exclu un bon nombre de coopératives et y a introduit des entités privées à finalité lucrative. Cet article s’intéresse au débat que cette situation suscite quant à la vision de l’ES véhiculée par ses représentations statistiques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".