Bibliographic record
Abstract
Human population and innovative technologies are increasing, creating growing waste in landfills. However, some waste products can be recycled and are recycled around the world. There are certain guidelines on proper recycling that have to be followed in order to achieve desired results. Yet, many people recycle incorrectly creating problems, such as contamination. Recycling contamination is a term referred to items placed in bins that cannot be recycled or materials disposed of in the wrong recycling carts (Vantol, 2011). Recycling contamination is a significant problem and is most common in multi-family dwellings (MFDs). To compare to single-family dwellings (SFDs), MFDs have lower participation rates and higher contamination rates (Vantol, 2011). The problem exists around the world. Many different levels of governments and corporations have tried to tackle the problem of contamination. In some cases proposed solutions were successful, however in some they were not. A municipal agency - The North Shore Recycling Program offers recycling services to North Vancouver. Their mission is “to make conservation second nature on the North Shore by moving the community from environmental awareness to sustainable action” (North Shore Recycling website). The agency comes across the problem of recycling contamination extremely often. Thus, they would like to be informed of the reasons behind increased recycling contamination rates in MFDs and solutions that were successfully used in other areas, as well as some that were not, in order to overcome the barriers the agency experiences.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".