Shining a light on fossil fuel subsidies at the WTO: how NGOs can contribute to WTO notification and surveillance
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
Abstract Fossil fuel subsidies undermine efforts to mitigate climate change, and they damage the trading system. Multilateral discussion is hampered by inconsistent definitions and incomplete data, which could increase the risks of WTO disputes. Members do not notify such subsidies as much as they should under the Agreement on Subsidies and Countervailing Measures (ASCM), which limits the usefulness of the SCM Committee. The reports of the Trade Policy Review Mechanism on individual countries and on the trading system draw on a wider range of sources, creating an opportunity for non-governmental organizations (NGOs) to provide the missing data from publicly available sources. We suggest a new template that could be used for such third-party notifications. The objective is to shine a light on all fossil fuel subsidies that cause market distortions, especially trade distortions. The result should be better, more comparable data for the Secretariat, governments, and researchers, providing the basis for better-informed discussion of the incidence of fossil fuel subsidies and rationale for their use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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