Transnational private governance between the logics of empowerment and control
Bibliographic record
Abstract
Abstract Transnational private governance initiatives that address problems of social and environmental concern now pervade many sectors. In tackling distinct substantive problems, these programs have, however, prioritized different problem‐oriented logics in their institutionalized rules and procedures. One is a “logic of control” that focuses on ameliorating environmental and social externalities by establishing strict and enforceable rules; another is a “logic of empowerment” that concentrates on remedying the exclusion of marginalized actors in the global economy. Examining certification programs in the areas of fair trade, organic agriculture, fisheries, and forest management, we assess the evolutionary effects of programs prioritizing one logic and then having to accommodate the other. The challenges programs face when balancing between the two logics, we argue, elucidate specific distributional consequences for wealth, power, and regulatory capabilities that private governance programs seek to overcome.
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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 | 0.016 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.045 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".