Let's Talk Trash: Zero Waste Initiatives in San Francisco and Toronto
Bibliographic record
Abstract
Our current society keeps consuming more and more, thereby generating increasing amounts of waste worldwide. There is growing realisation among policy-markers that landfill disposal is not sustainable, and thus that better waste management is needed. Some solutions have been elaborated, among which the sustainable concept of sending no more waste to landfill, or “zero waste”. Several cities have attempted to adopt this concept; Toronto and San Francisco are two of them. This thesis seeks to analyze how policy makers in both cities implement the zero waste concept in their cities, and the socio-political obstacles faced along the way. The study conducts a thorough textual analysis of both official and non-official sources, following a critical discourse analysis method. It identifies recurrent discursive and decisional patterns of waste diversion promotion, while revealing some lacks of consistency in encouraging actual changes in waste consumption. The thesis elaborates on how each city’s socio-political context have played in the implementation of the zero waste-to-landfill initiatives. The thesis finds that underlying conflicting motivations might have influenced the whole evolution of the initiatives in both cities, which are far from having reached their goals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".