Credibility dilemmas under the Paris agreement: explaining fossil fuel subsidy reform references in INDCs
Bibliographic record
Abstract
Fossil fuel subsidies are a market distortion commonly identified as an obstacle to decarbonization. Yet due to trenchant political economic risks, reform attempts can be fraught for governments. Despite these concerns, an institutionally and economically diverse group of states included references to fossil fuel subsidy reform (FFSR) in their Intended Nationally Determined Contributions (INDCs) under the Paris Agreement. What conditions might explain why some states reference politically risky reforms within treaty commitments, while most others would not? We argue that the Article 4 process under the Paris Agreement creates a "credibility dilemma" for states-articulating ambitious emissions reduction targets while also defining national climate plans engenders a need to seek out appropriate policy ideas that can justify overarching goals to international audiences. Insomuch as particular norms are institutionalized and made salient in international politics, a window of opportunity is opened: issue advocates can "activate" norms by demonstrating how related policies can make commitments credible. Using mixed methods, we find support for this argument. We identify contextual factors advancing FFSR in the lead-up to the Paris Agreement, including norm institutionalization in regimes and international organization programs as well as salience-boosting climate diplomacy. Further, we find correspondences between countries targeted by transnational policy advocates and FFSR references in INDCs, building on the momentum in international politics more generally. Though drafting INDCs and NDCs is a government-owned process, the results suggest that understanding their content requires examining international norms alongside domestic circumstances.
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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 | 0.021 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".