Legal frameworks for the social and solidarity economy
Bibliographic record
Abstract
The OECD Global Action “Promoting Social and Solidarity Economy Ecosystems”, funded by the European Union, through its work stream on legal frameworks, endeavours to: 1) increase knowledge and understanding on legal frameworks for the social and solidarity economy; 2) explore approaches and trends of legal frameworks to regulate the social and solidarity economy as a whole and social economy organisations; and 3) understand how legal frameworks can be used to promote and develop the social and solidarity economy in different contexts. This paper defines the legal notions, traditions and approaches to better understand legal frameworks that regulate the field. It presents and analyses the diversity, relevance and implications of legal frameworks that regulate the social economy; takes stock of the processes that lead to their design and implementation; identifies possible criteria for assessing their performance; and highlights the crosscutting issues and policy examples that could inspire countries.
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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 | 0.014 | 0.017 |
| 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 | 0.032 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.016 | 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".