Bibliographic record
Abstract
Some subsidies (such as for fossil fuels and fisheries) adversely affect global public goods (such as a stable climate and the maintenance of global fish stocks); others affect global price levels (domestic support for certain agriculture commodities), or have negative consequences for a trading partner. World Trade Organization (WTO) members have negotiated an agreement on subsidies, but there are severe limits to that agreement’s ability to exercise discipline, and the prospects of its amendment remain limited. This article examines whether states can improve discipline through the use of informal mechanisms and, if so, under what conditions. Informal discipline on subsidies depends on the existence of fora to discuss definitions, generate information about their incidence, discuss whether a particular measure fits the definition, and consider whether a remedy exists. This article takes international organizations (IOs) seriously as fora for generating ‘law’, not simply as bodies exercising power or coercion, and it explores a particular view of law. If codification is not the only indicator of law, if one accepts that law also emerges in social interaction, then we must attend to the less formal places where the law of subsidies emerges, and affects state actions. The analysis of where disciplines might be found is based on a three-level set of comparisons: (i) within the WTO, involving horizontal compared to sectoral disciplines, with a focus on committee and other peer-review processes, rather than the traditional focus on the dispute settlement system; (ii) the WTO compared to, and in complement with, other IOs addressing particular sectors; and (iii) IOs compared to, and in complement with, non-governmental organizations. The article provides four case studies involving subsidies: (i) export credits, (ii) shipbuilding, (iii) fisheries, and (iv) fossil fuels. It assesses variations in number of actors, the conceptualization of the problem, definitions, obligation, data, and organizations across these case studies and the impact of such differences on the development of subsidy disciplines.
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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 | 0.019 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".