E‐waste Management Programmes and the Promotion of Design for the Environment: Assessing Canada's Contributions
Bibliographic record
Abstract
In recent years, legislatures across the world have turned their attention to the escalating amount of electronic and electrical waste, and their accompanying environmental threats. Increasing consumption of electronic and electrical equipment (EEE) and the indiscriminate disposal of used products contribute to the problem furthered by designs that ignore durability and support the limitless use of toxic substances. One proposed method of changing this trend is to stimulate producers to design for the environment (DFE). In many ways DFE breaks the traditional physical barriers for design and requires a vision of the product for its entire life cycle. As Canada's provincial and federal governments move to respond to the problem of e‐waste, their chosen approaches are critically analysed. In particular, this article investigates how the provinces of Alberta, Saskatchewan, British Columbia, Nova Scotia and Ontario conceptualize the problem of e‐waste. In addition, the extent to which the policy goals and financing mechanisms incorporated in each programme adequately consider the role of DFE is evaluated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".