Bibliographic record
Abstract
The title of this thesis is ``The Effect of Environmental Regulations on Health and Labor Supply: Evidence from Ontario's Coal Phase-out". It explores the effect of environmental regulations on a wide range of health, and economic outcomes. I use coal phase-out in Ontario, Canada, as a quasi-experimental setting in my study. The first chapter of my thesis is introduction. Then, I explore related works, and conduct a literature review on papers that have studied the effect of pollution on air quality, infant health, adult health, environmental justice, labor supply, income, and productivity. In the third chapter, I present the historical background, and discuss implementation of coal phase-out in Ontario, in detail. In the fourth chapter, I use data from pollution monitoring networks to estimate the impact of Ontario's coal phase-out on the local air quality. I apply a difference-in-differences strategy comparing air pollution concentrations within 20 miles of power plants relative to 20-40 miles before and after their shutdowns. I find that applying this policy decreases O3, and SO2 levels by 6, and 19 percent, respectively. However, the results do not show a statistically significant effect on PM2.5, NOx, NO2, and NO levels. In the fifth chapter, I study the effect of Ontario's coal phase-out on infant, and adult health outcomes such as, birth weight, low birth weight incidence, preterm birth, adult's respiratory, and cardiovascular diseases. I use Canadian Vital Statistics-Birth and Death Databases, and a difference-in-differences strategy. My findings show that coal-fired power plant closures do not significantly change infant, and adult health outcomes. The final chapter, investigates the effect of coal phase-out in Ontario on local migration, labor supply, and income. I use a large-scale panel dataset, Longitudinal Administrative Databank (LAD), and a difference-in-differences method to find the causal relationships. I find that closure of coal-fired power plants in Ontario does not have any significant effect on local migration, and labor supply, on the extensive margin. However, it is associated with a 2.6-3 percent increase in employment income, and a 0.7-0.8 percent increase in market income in the short-, and the long-run, respectively.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".