The worldwide making of the social economy
Bibliographic record
Abstract
The concept of ‘social economy’ assembles diverse initiatives, like cooperatives, associations, mutual societies, foundations and other member-based organizations. These initiatives share common characteristics: they are autonomous organizations and enterprises; they value service to the community over profit; they rely on voluntary participation and democratic governance.\n\nWhere markets and states fail, social economy organizations bring about social innovation and change. Social economy initiatives intend to answer to people’s needs and aspirations, always and everywhere.\n\nFor a better knowledge and understanding of the social economy, this book offers a broad view on the recent changes and innovations in Africa, Asia, Europe and Latin America. The contributions cover various topics, such as social protection, fair trade and microfinance. Several chapters deal with the delicate relation with the state (in Canada, the UK, the Netherlands, Sweden, Brazil and Venezuela); others present a special focus on important new regional dynamics (in Africa, China, Europe and the United States).\n\nWith contributions of scholars from around the globe, the book clearly demonstrates that in a range of contexts and regions social economy organizations and enterprises are reinventing themselves, proposing social innovations and bringing about substantial social change.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".