Bibliographic record
Abstract
Annales de l'économie publique, sociale et coopérative Women leading the charge in the social and solidarity economy: A snapshot of gender perceptions of entrepreneurship MAríA BAstidA, AlBerto VAquero GArcíA, MiGuel ÁnGel VÁzquez tAín and MArisA del río ArAújo Failure of cooperative self-regulation: An exploration of cooperative regulatory violations cAleB M. Houston and jenniFer d.HAMrick Pathways towards member participation in governance of cooperatives: conjunction of motivations and resources in the case of French community energy Adélie rAnVille does cultural difference impede the allocation of government procurement?evidence from china Wenqi li, YiPinG Wu and jinYu Wu the impact of joint liability lending on leveraging social capital WeijiA WAnG and HAnYinG qi communication, principal-agent alignment and performance: evidence from Brazilian agricultural co-operatives celinA MArtinez GeorGes, jAsPer GrAsHuis, silViA MorAles de queiroz cAleMAn and GuilHerMe FoWler de AVilA Monteiro A population-level approach to distributional weighting dAniel j.AclAnd and steVen rAPHAel 'it's ours': understanding the aspects of ownership in financial cooperatives MurHulA cuBAkA PAtrick and BAleMBA kAnYurHi eddY
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.913 | 0.825 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".