Bibliographic record
Abstract
The World Trade Organization (WTO), established in 1995, adjudicates "trade disputes" between member nations in cases with human rights, cultural, environmental, and public health significance. Throughout the resolution process and even after a case's conclusion, little of what happens is made accessible to the public. However, it is one thing to criticize the WTO for its lack of transparency from outside the process and another to critically examine what was withheld from disclosure and what dangers that presents. This is the inside story from a scientific adviser to one party in a WTO case, who analyzes what happened from a public health point of view. The analysis concludes that the public health justification for banning asbestos was accepted in the end by WTO economists, despite the WTO's bias in favor of the party (Canada) making the free trade challenge (to public health legislation), despite the WTO's lack of expertise in science, medicine, engineering, and public health, and despite important erroneous statements made to the WTO under the cover of confidentiality. The case nevertheless illustrates that the WTO's threat to national sovereignty could never withstand the light of day if the limitations and dangers of the process were open for all to see.
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 | 0.035 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.048 | 0.024 |
| Insufficient payload (model declined to judge) | 0.004 | 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".