Extended Producer Responsibility in Niagara’s Business Sector
Bibliographic record
Abstract
While Niagara’s economic growth and various initiatives such as the Economic Growth Strategy are vital to the Region, environmental and social considerations are also paramount. The Niagara Region’s Waste Management Advisory Committee would like to encourage the Niagara Economic Development Corporation to consider principles of Extended Producer Responsibility (EPR) and Design for the Environment (DFE) in local business/industry development policies and programs. As an advisory committee of Niagara Regional Council, the purpose of the Waste Management Advisory Committee (WMAC) is to provide advice and recommendations that will facilitate the implementation of the Region’s Long Term Waste Management System. WMAC is comprised of members of the community at large and a representative from the Ontario Federation of Agriculture. Environmental stewardship is a clear priority for this Committee and should be a fundamental concept for all business/industry. Business/industry should assume a greater responsibility for ensuring that the manufacturing processes and products which are manufactured, used or disposed of in Niagara, have a minimum impact on the environment.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".