Do environmental regulations reduce greenhouse gas emissions? A study on Canadian industries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper uses the Canadian industrial macro-level data from CANSIM to investigate the effect of formal and informal regulations on pollution intensity. Proxies for formal and informal regulation variables are defined as in Cole et al., 2005. The econometrics model is a panel with 23 manufacturing industries over 10 years, from 1994 to 2003. Manufacturing industries are chosen because they are the most pollutant industries. It is found that formal and informal regulations have significant effects on decreasing the direct and indirect greenhouse gas emissions in Canadian industries. Provinces with younger populations have stricter informal regulation on pollution density, because younger populations care more about the future quality of the environment. Also, provinces with a higher rate of unemployment have less formal regulation on pollution density; for those provinces, providing employment for citizens is more important than providing a healthy environment. Wealthier provinces with a low employment rate face less pressure from society and can spend more money on the environment; therefore, they have lower pollution density. Furthermore, industries with large average firm size can decrease emissions more than other industries. The cost of controlling the emissions decreases with firm size because of economies of scale.
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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) | 0.000 | 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) | 0.003 | 0.002 |
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 it