Potential Effects of Single Use Plastics Ban on Ontario Manufacturers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
During the past few decades, plastics pollution has become a global concern. Governments are striving to find the best way to reduce plastics consumption and waste. The Government of Canada has proposed a ban on single-use plastics to be implemented in 2021, a potentially disruptive public policy. Many studies have been conducted on the environmental impacts of plastics and the benefits of a plastics ban, but little has been written about the potential effects of these policies on plastics manufacturers. An economic model was developed to analyze the effects on Ontario single use plastics manufacturers. Results of the model show that most plastics manufacturers would be able to recover their investments within three years for the costs of converting to an alternative material. However, there is an aggregated cost on manufacturers of approximately $262 million for the first three years. Additionally, a small number of specialized manufacturers would not be able to recover from the ban, potentially leading to some job losses. Overall, however, the results indicate that manufacturers would be able to adjust to the ban in the longer-term, providing for the environmental benefits of reduced plastics consumption and waste.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it