Canada Wide Standard for Particulate Matter and Ozone: Cost‐Benefit Analysis Using a Life Quality Index
Bibliographic record
Abstract
The adverse impacts of particulate air pollution and ground-level ozone on public health and the environment have motivated the development of Canada Wide Standards (CWS) on air quality. In cost-benefit analysis of air-quality options, valuation of reduction in mortality is a critical step as it accounts for almost 80% of the total benefits and any bias in its evaluation can significantly skew the outcome of the analysis. The overestimation of benefits is a source of concern since it has the potential of diverting valuable resources from other needs to support broader health care objectives, education, and social services that contribute to enhanced quality of life. We have developed a framework of reasoning for the assessment of risk-reduction initiatives that would support the public interest and enhance safety and quality of life. This article presents the Life Quality Index (LQI) as a tool to quantify the level of expenditure beyond which it is no longer justifiable to spend resources in the name of safety. It is shown that the LQI is a compound social indicator comprising societal wealth and longevity, and it is also equivalent to a utility function consistent with the basic principles of welfare economics and decision analysis. The LQI approach overcomes several shortcomings of the method used by the CWS Development Committee and provides guidance on the compliance costs that can be justified to meet the Standards.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".