Modern Society, Technology and Electronic Waste: Who Should Be Responsible?
Bibliographic record
Abstract
Electronic waste (e-waste) in modern society is a growing issue that creates risks by degrading natural resources, through the production of the electronic devices in question, but also at a later end-of-life stage when recycled irresponsibly; by harming individuals directly – those who partake in the recycling, but also indirectly when deadly toxins from recycling flow into water and soil sources. This thesis looks specifically at the recent progression into modern society and associated risks as can be linked to the environmental problem of e-waste in Ontario, Canada. It looks at individuals as consumers in society and examines their knowledge about the increasingly prevalent solution of Extended Producer Responsibility (EPR) as it should perhaps be used as a solution in Ontario. Through the use of semi-structured interviews with consumers – and considering the objective variable of government structure in Canada and Ontario that affects consumer views about e-waste; this study aims to understand what individuals think would work best in Ontario, a state-led directive or an EPR-based solution.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.040 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".