Sustainability Impact Assessment of Trade Agreements: From Public Dialogue to International Governance
Bibliographic record
Abstract
In common with the governments of the United States and Canada the European Commission subjects its trade policy to a publicly conducted impact assessment process. The EC approach differs from the others in assessing economic and social impacts as well as environmental ones, in other countries as well as domestically. In principle this can contribute to strengthening international governance. In practice difficulties are encountered in integrating the studies into the decision-making process. This paper examines the experience that has been accumulated in the EC programmme, with particular reference to studies at the global level for World Trade Organisation negotiations and regionally for the Euro-Mediterranean Free Trade Area. These two examples offer pointers for how the impact assessment process might be adapted or extended to make a stronger contribution to international governance at both regional and global level.
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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 | 0.078 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.032 | 0.025 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".