Bibliographic record
Abstract
Proposals: • Create or use an online social network or platform as a tool to help facilitate rating and complaints based enforcement for business recycling. This will provide both outreach and education as well as a centralized place in the Greater Vancouver Region for data collection and communication between stakeholders • Facilitate the creation of a bylaw for mandatory commercial recycling or by adding a clause to existing bylaws to include businesses in current mandatory recycling practices • Outline responsibilities between stakeholders, particularly for small-medium sized businesses Academic Findings: • Target small-medium sized businesses because they have the least financial and human resources to spend time improving their waste practices • Support policy tools with outreach, especially targeting lower income zones and smaller businesses • Recycling programs will only be successful if they are convenient, low cost and efficient for all stakeholders Interview Findings: • From the municipalities interviewed, case-by-case solutions such as lottery system, franchising, mandatory service fees and enforcement are needed because most of the business sector waste and recycling collection is currently being provided by private haulers. All stakeholders should be taken into account when coordinating these compromises • Soft enforcement methods such as education work best and fines are only used as a last resort for business that refuse to comply • Front loading trucks most efficient and would allow expansion of collection service, but this requires large initial investment • Communication is needed between stakeholders: businesses, haulers, processing facilities and municipalities.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".