Paper Recycling at Queen’s University and its Waste Implications
Bibliographic record
Abstract
The procurement and disposal of paper commodities presents a unique case in respect to municipal solid waste at Queen’s University at Kingston, ON. Using Queen’s University Admissions viewbook & Queen’s Alumni Review magazine as a case study, this thesis investigates how the procurement, distribution, and disposal of these paper commodities can be altered to better align with the Resource Productivity & Recovery Authority’s, Ontario Regulation 391/21, made under the Resource Recovery & Circular Economy Act, 2016. The aim of this project was to investigate whether printing volumes of these products were altered upon the onset of Covid-19, and how the lifecycle of these publications creates environmental implications. Using primary and secondary research, I concluded that a complex pathway exists in the end-of-life management of these products, due to their composition, and thus, compatibility with Kingston, ON, recycling programs. As such, alternatives to these documents including an online format present a more sustainable medium-- should these commodities continue to be produced. However, a purely digital delivery of these documents also displays environmental concerns, preventing Queen’s University from reaching its highest potential to align with the Resource Productivity & Recovery Authority’s legislation related to individual producer responsibility (IPR).
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".