Quantification of improperly disposed mercury containing lights in Canadian households
Bibliographic record
Abstract
Mercury containing lamps (MCL), often classified as household hazardous waste, are a threat to human and environmental health. Extended Producer Responsibility (EPR) is a common management framework. The objectives of this study are to estimate the improper disposal of household MCLs across eight Canadian provinces (with and without EPR) and model households’ improper MCL disposal using seven factors. The number of retail locations collecting lamps per 100,000 households is about 10 in provinces with EPR, and about 3 in provinces without EPR. Across all study areas, MCLs being disposed of in landfills are decreasing over time. Pearson correlation analysis found that environmental awareness and socio-economic factors are more important to electronic light usage in provinces with EPR. Regression analysis showed that the percentage of households using LEDs was important in determining the disposal of MCLs in provinces with and without EPR. For provinces with existing EPR programs for MCLs, the percentage of households composting kitchen waste was important. This may be due to household members being more environmentally aware. In non-EPR provinces, obtaining a tertiary education was important in determining the disposal of MCLs. EPR is an effective tool in the management of MCL waste in Canada. The conventional MCL per capita variable may be less useful given the changing household size. We recommend monitoring and reporting of the MCL quantity at the household level for policy-making purposes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".