Bibliographic record
Abstract
The Comprehensive Economic and Trade Agreement (CETA) between the EU, its Member States and Canada has been presented as “the best trade agreement the EU has ever negotiated”. While there are certainly many advantages compared to older trade treaties, two remaining points of concern are investigated in this contribution. The first one relates to the manner in which the EU utilises its own system for ensuring that sustainability concerns are integrated into trade agreements. In the first part of this contribution, it is investigated whether the manner in which the integration instrument is employed in the case of CETA, notably where the inclusion of an investor state dispute settlement (ISDS) mechanism is concerned, is in line with consistent, evidence-based policy choices and with the self-imposed guidelines as laid down in the so-called Trade Sustainability Impact Assessment (TSIA) Handbook. The second part of this contribution investigates whether the continued implementation of the precautionary principle on the side of the EU is properly secured in the view of the various rules, procedures and institutional arrangements contained in the CETA text. In that respect, the findings of a detailed study on this topic are summarised first, after which some of the critique from the side of the Dutch Minister of Foreign Trade and Development Cooperation and from the EU Commissioner for Trade is examined and commented upon.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".