Bibliographic record
Abstract
This chapter classifies seven competitive advantages : i) Bargaining power, ii) The sharing of costs, iii) Higher productivity, iv) Lower prices of outputs, v) The transformation of non-standard jobs into standard jobs, vi) The generation of formal ‘part-time’ jobs, and vii) The promotion of social capital. In order to contextualize this competitiveness within a broader market setting, it is also necessary to analyze the strengths of cooperatives’ competitors, namely, conventional companies. Conventional companies have two strengths : the capacity to mobilize large capital volumes and the possession of rapid decision-making mechanisms. Against this backdrop, it should be noted that the main battleground between cooperatives and conventional companies lies in labor-intensive sectors, since cooperatives have difficulties in entering capital-intensive sectors. Importantly, in labor-intensive sectors, cooperatives are highly likely to have an upper hand over conventional companies . In such sectors, conventional companies lose their two strengths against cooperatives, whereas cooperatives maintain their seven strengths against conventional companies. Empirical analyses of enterprises in several countries, such as the United Kingdom, France, Canada, Portugal, and Uruguay, confirm that the survival rates of cooperatives are higher than those of conventional companies.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads 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".