National Policy and Transnational Governance of Climate Change: Substitutes or Complements?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many scholars and policymakers see transnational governance as a substitute for lackluster national and international policies, particularly in the context of intergovernmental gridlock or limited state capacity. The bulk of the literature explains sub- and non-state actors’ participation in transnational initiatives as a product of, on the one hand, micro-level incentives and, on the other, diffusion processes that create and spread normative and market-based pressures. We argue that such theoretical perspectives overlook the dynamic relationship between national policies and transnational governance. First, we argue that ambitious national policies positively affect sub- and non-state actors’ participation in transnational governance. Second, we posit that domestic institutions condition the effects of micro-level incentives and transnational pressures on participation in transnational governance. We test these claims in the climate regime, using an original dataset that, for the first time, measures cross-national participation in transnational climate initiatives across jurisdictions. The results support our expectations. They therefore suggest that we should understand national policies and transnational governance as complements, rather than competitors, to one another. Finally, by showing how and when national policies affect participation in transnational initiatives, we identify important scope conditions for their significance in addressing climate change.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it