Investigating the impacts of plausible Canadian policies and their supporting mechanisms on export-based regional air pollution in China: A cement manufacturing case study
Bibliographic record
Abstract
The Canadian Environmental Protection Act (CEPA) enables the Minister of Environment and Climate Change to develop policy to curtail international air pollution. However, regional air pollution generated during the manufacturing of products outside of Canada is not addressed in CEPA. Using cement manufacturing in China as a case study, three policy options were devised to manage export-based regional air pollution. The options investigated included Policy 1—an open border with direct support for domestic cement manufacturers, Policy 2—a restricted border with no support for domestic cement manufacturers, and Policy 3—a selective border with partial support for domestic cement manufacturers. An analytic hierarchy process, in conjunction with the three actionable solidarities of cultural theory, was applied to the policy options and their supporting mechanisms. Results indicated that Policy 3 was strongly favoured (52.5%), followed by Policy 2 (33.4%), with Policy 1 being the least favoured (14.2%). Regarding policy mechanisms, a verification process was preferred by all three solidarities. From the standpoint of a universal approach to trade it is recommended that an air quality agreement between China and Canada under CEPA be established with a framework to eventually incorporate environmental production declarations. With respect to cement exports, it is recommended that manufacturers in China provide emissions intensities and winter smog assessments.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".