Regulating Ontario’s circular economy through food waste legislation
Bibliographic record
Abstract
Purpose Ontario’s Ministry of Environment and Climate Change seeks to legislate diverse waste streams (including food waste) by implementing Bill 151, known colloquially as the Waste Free Ontario Act. The purpose of this study is to investigate how stakeholders in Ontario’s food and waste systems perceive the prospective legislation. Design/methodology/approach The paper is based on interviews with stakeholders across the food value chain in Ontario, as well as an analysis of legislation and related documents. Findings The paper argues that Bill 151 represents the Province’s commitment to an ecological modernization paradigm. This research uncovers the lines of tension that may exist in the implementation of food waste policy. These lines of tension represent stakeholders’ ideological perspectives on food waste, including whether it signals an efficient or inefficient economy, whether legislation should prioritize economic or environmental goals and whether it is more appropriate for legislation to incentivize desired food waste treatments or penalize/prohibit undesired activities. Originality/value The analysis reveals potential allies in the regulatory process, likely points of contention and areas where greater consensus may be forged, depending on government efforts to reframe the issues at stake.
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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".