Democracy and Enterprise. A Philippine Cooperative Balances Social and Business Demands
Bibliographic record
Abstract
A central concern of the social enterprise literature is the tension between an organization’s social and its business mission. This paper argues that cooperatives avoid this tension because organizational decisions are made by the social beneficiaries – the cooperative members. This is demonstrated with the experience of Sorosoro Ibaba Development Cooperative (SIDC) in the Philippines. SIDC started in 1969 with 59 small farmers each contributing US$ 10. SIDC now offers a range of social and economic services to nearly 18,000 members with assets reaching US$ 36 million in 2012. However SIDC currently faces very important challenges, the most formidable of which is the increasingly globalised production and consumption system. SIDC has adjusted to market pressures not by internationalising its markets, investment, management and resources but through vertical integration of its domestic supply chain, adoption of technological innovations and by tapping migrant workers’ savings. However, globalisation also means that SIDC products and services compete with those produced without concern for workers’ safety, local employment or environmental health. The threat is exacerbated by trade agreements that erode state capacity to temper the corporate drive for profit maximisation with peoples’ right to employment, living wage, and a healthy environment
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".