Resisting Transparency: Corruption, Legitimacy, and the Quality of Global Environmental Policies
Bibliographic record
Abstract
The domestic endorsement and institutionalization of transparency is of central importance to the implementation of global environmental policies. Studies often contend that interaction with international organizations (IOs) promotes domestic support for transparency. This article qualifies this conclusion and suggests that the positive effects of interaction with international organizations depend on the quality of IO decision-making processes, defined as their fairness, predictability, and effectiveness. Unfair, ineffective, and unpredictable decision-making processes in IOs can increase corruption, reduce legitimacy, and make officials blame transparency for unsatisfactory decision-making. The results build on a study of government officials in developing countries responsible for managing funds from the Clean Development Mechanism and the Multilateral Fund for the Implementation of the Montreal Protocol. Our findings suggest that government officials who perceive IO systems as unfair, ineffective, and unpredictable cultivate an adversarial relationship with media and NGOs and become more critical of the benefits of transparency.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".