Trade sustainability impact assessment (SIA) on the comprehensive economic and trade agreement (CETA) between the EU and Canada: Final report
Bibliographic record
Abstract
Commissioned by the European Commission, the Final Report for the EU-Canada Sustainability Impact Assessment (SIA) on the EU-Canada Comprehensive Economic and Trade Agreement (CETA) provides a comprehensive assessment of the potential impacts of trade liberalisation under CETA. The analysis assesses the economic, social and environmental impacts in Canada and the European Union in three main sectors, sixteen sub-sectors and across seven cross-cutting issues. It predicts a number of macro-economic and sector-specific impacts. The macro analysis suggests the EU may see increases in real GDP of 0.02-0.03% in the long-term from CETA, whereas Canada may see increases of 0.18-0.36%. The Investment section of the report suggests these numbers could be higher when factoring in investment increases. At the sectoral level, the study predicts the greatest gains in output and trade to be stimulated by services liberalisation and by the removal of tariffs applied on sensitive agricultural products. It also suggests CETA could have a positive social impact if it includes provisions on the ILO’s Core Labour Standards and Decent Work Agenda. The study also details a variety of impacts in various “cross-cutting” components of CETA. It finds CETA would stimulate investment in Canada, and to a lesser extent in the EU; and finds costs outweigh the benefits of including controversial NAFTA-style investor-state dispute settlement (ISDS) provisions in CETA. It predicts potentially imbalanced benefits from a government procurement (GP) chapter. The study assumes CETA will lead to an upward harmonisation in intellectual property rights (IPR) regulations, particularly in Canada, which will have a number of effects. It predicts some notable impacts in terms of competition policy, as well as trade facilitation, free circulation of goods and labour mobility.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".