2 Air Pollution, Health and Mortality: Separating Fact from Fiction
Bibliographic record
Abstract
In the last few years, Ontarians have been repeatedly told that the people who supply our electricity are mass murderers. This eye-popping accusation does not come the radical fringe, but from banks, churches, industry groups, unions, Environment Canada, school groups, the Ontario Medical Association (OMA), and numerous others, via the umbrella group the Ontario Clean Air Alliance (OCAA). 1 Here is what the OCAA says about our coal-fired power plants: The Ontario Medical Association estimates that air pollution costs Ontario more than $10 billion per year in health care costs, lost work time and other quantifiable expenses, as well as killing an estimated 2,000 Ontarians each year. The OMA has declared air pollution "a public health crisis " in Ontario. Coal-fired power plants are the single largest industrial contributors to this crisis.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".