Confronting trade‐offs and interactive effects in the choice of policy focus: Specialized versus comprehensive private governance
Bibliographic record
Abstract
Abstract In setting standards for responsible business practices, certification programs create issue boundaries delineated by the focus of their standards. These issue boundaries may impede action on certain causes of problems (i.e. problem interactive effects) or lead to policy actions that affect other governance initiatives (i.e. policy interactive effects). When these interactions are extensive, programs confront trade‐offs: develop as a comprehensive program (i.e. have a broad policy focus) and take on higher internal administrative costs, or develop as a specialized program (i.e. have a narrow policy focus) and undertake to develop mechanisms to facilitate across‐program coordination. This paper explores these trade‐offs. It examines the origins of the different policy foci of coffee, forest, and fisheries certification programs, and identifies five strategies that programs are currently using to manage policy and/or problem interactive effects. Then, informed by research in public administration and international relations, it details additional approaches for improving issue‐boundary management.
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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 | 0.033 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".