The WTO, Science, and the Environment: Moving Towards Consistency
Bibliographic record
Abstract
Governments are increasingly using taxes to address a variety of environmental concerns. World Trade Organization (WTO) rules recognize that, like regulatory instruments, governments may use taxes for protectionist purposes. The rules are designed to prevent protectionist behaviour while allowing use of such instruments for genuine purposes such as environmental protection. Interestingly, however, there are some notable anomalies in the rules arising from differential evidentiary requirements in different situations. First, the rules are different depending upon whether a country's measure aims to protect on one hand human, animal, or plant health; or on the other, the environment. Second, the rules are stricter where a country's measure takes the form of a regulation than where it takes the form of a tax. The article argues that there is no principled rationale for the differential evidentiary requirements by instrument (regulation versus taxes) or area (health versus environment) but finds that there may be both a historical and political economy explanation. It also discusses the desirability for consistency in WTO law across instruments and risk-related policy areas.
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.
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 | 0.124 | 0.187 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.051 |
| Scholarly communication | 0.026 | 0.033 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.023 | 0.037 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".