An SIA analysis of the Investment Chapter in the EU-Canada Comprehensive Economic and Trade Agreement (CETA)
Bibliographic record
Abstract
This study is a section from the Sustainability Impact Assessment (SIA), commissioned by the European Commission, on the impacts of the Investment Chapter in the EU-Canada Comprehensive Economic and Trade Agreement (CETA). The Investment Chapter in CETA could encourage economic benefits including trade-stimulating effects and fostering intangible business linkages in Canada, although the significance of these will likely be minor to notable at most; impacts in the EU will likely follow these trends but on an even lower level of significance. Positive environmental impacts would result from increased investment in green technologies, yet negative impacts would likely result from increased FDI in the oil sands and mining sectors in Canada. Various social impacts are expected, but all relatively minimal in scale. The majority of the study is devoted to investigating the costs vs. the benefits of including controversial NAFTA-style investor-state dispute settlement (ISDS) provisions in CETA. It find that there is no solid evidence to suggest that ISDS will maximise economic benefits in CETA beyond simply serving as one form of an enforcement mechanism, just as state-state dispute settlement is also an enforcement mechanism. And the policy space reductions caused by ISDS allowances in CETA, while less significant than foreseen by some parties, would be enough to cast doubt on its contribution to net sustainability benefits. As such, the study’s assessment suggests that a well-crafted state-state dispute settlement mechanism might be a more appropriate enforcement mechanism in CETA than ISDS.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".