Bibliographic record
Abstract
The importance of co-operation between disputing parties Co-operation between the disputing parties will often be key to the successful resolution of a scientific or technical dispute, and may also allow for a calibrated application of the precautionary principle that may not be as achievable through adjudicatory dispute settlement. Whether or not disputants ultimately do co-operate effectively cannot by any means be guaranteed, but judicial prompting may assist. The two awards in the well-known Trail Smelter Arbitration (US v. Canada) provide an early demonstration of how helpful it may be to allow time for co-operative study of how to address or ameliorate a problem, here the distribution of sulphur dioxide from the Canadian smelter at Trail through cross-border currents in the upper air. In its first award the Tribunal decided that three consultants would be appointed for the gathering of meteorological observations, and prescribed a temporary emissions limitations regime. In its second award the Tribunal was then in a position to lay down a detailed and permanent regime. Adjudicatory proceedings may be just one of the stages through which a dispute proceeds, and it is part of the function of an international court or tribunal to take this into account in deciding how to deal with a case. The practical significance of scientific and administrative co-operation is apparent upon considering the various high-profile international disputes involving scientific uncertainties introduced in the pages that follow.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.048 | 0.019 |
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".