Comprehensive Economic and Trade Agreement (CETA) and air pollution
Bibliographic record
Abstract
The study empirically investigates and shows that on average, the implementation of the Comprehensive Economic and Trade Agreement (CETA) may contribute in the fight against global warming. This study finds that on average, a 1 percent increase of a percentage point in the bilateral volume of trade as a portion of GDP between Canada and a typical EU member could help reduce annual per capita emissions of GHGs in an average CETA member by about .57%. The results also show that the presence of CETA may decrease annual per capita emissions of GHGs in almost all CETA members. There is no statistically significant evidence suggesting an increase of GHGs per capita emissions in any CETA member, regardless of the model or statistical method employed in the paper. These results stand because of the combinations of the factor endowment hypothesis (FEH), the pollution haven hypothesis based on population density variations (PHH2) and the pollution haven hypothesis based on national income differences (PHH1) between each EU member and Canada.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".