A Study of E-Waste Management Programs: a Comparative Analysis of Switzerland and Ontario
Bibliographic record
Abstract
Electronic waste (e-waste) is being generated around the globe at a high rate. High market penetration of electrical and electronic equipment (EEE) and the fast development of more innovative designs by producers and manufacturers on a regular basis make the current electrical and electronic equipment obsolete faster than before, which contributes towards the generation of more e-waste. To combat the issue, e-waste management programs are being developed, implemented, or evaluated in many jurisdictions around the world. Ontario is one of the jurisdictions that have taken initiatives and implemented an e-waste management program to address the rising quantity of e-waste. This thesis evaluates the Ontario's e-waste management program by using Logical Framework Approach (LFA) as an evaluation framework, and focusing on the criteria for a normative e-waste management program. It utilizes the Swiss e-waste management program as a case study to provide a comparative analysis, and extract valuable lessons through the application of the lesson-drawing approach that can be applied to improve the effectiveness of the implemented e-waste management program in Ontario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".