Residents' perception and worldview about radon control policy in Canada: A pro-equity social justice lens
Bibliographic record
Abstract
Radon is a potent indoor air pollutant, especially in radon prone areas and in countries with long winters. As the second top lung carcinogen, radon is disproportionately affecting certain population subgroups. While many provinces have taken sporadic actions, the equity issue has remained unaddressed across all policy measures. Attempts to enforce radon guidelines and enact building regulations without considering residents' views have proved ineffective. Research linking residents' radon risk perception and worldviews regarding radon control policy is lacking in Canada. We applied mixed (quantitative and qualitative) methods in a pro-equity social justice lens to examine the variations in residents' risk perception, access to risk communication messages, and worldviews about risk management across the sociodemographic strata. Triangulation of the quantitative and qualitative findings strengthened the evidence base to identify challenges and potential solutions in addressing the health risk through upstream policy actions. Enacting radon control policy requires actions from all levels of governments and relevant stakeholders to ensure equal opportunities for all residents to take the preventive and adaptive measures. Small sample size limited the scope of findings for generalization. Future studies can examine the differential impacts of radon health risk as are determined by various sociodemographic variables in a representative national cohort.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".