Bibliographic record
Abstract
The University of British Columbia (UBC) has been one of the leaders in sustainable practices on university campuses across Canada. Over the past few years, UBC has been working towards becoming a zero waste campus. One of the most limiting factors that is working against the overarching goal of becoming zero waste, is the fee structure that is currently in use for ancillary buildings hosted on campus. The fee structure charges ancillary buildings less for disposing of their garbage waste stream, than their organics waste stream. This provides an internal incentive for buildings to dispose of more garbage than organics to minimize their bottom line. In order to eliminate this disincentive program, the fee structure needs to be reevaluated. It is essential to focus on industry best practices before introducing a new fee structure on UBC campus, because ancillary buildings are able to opt out of UBC waste management in order to use a private waste disposal company. There are a number of cities and university campuses who have set applicable precedent when it comes to waste management practices, including the fee structures used in specific jurisdictions. San Francisco, Seattle, City of Vancouver, University of Western Ontario and the University of Victoria were all investigated in order to establish some industry best practices for achieving zero waste. Within the municipalities, residential waste collection rates were analyzed for trends that would incentivize zero waste practices. San Francisco has in place a discounting model that offers a decrease in rates for customers with a higher waste diversion rate, which has proven to be effective. Seattle offers discounts for bulk waste disposal of each of their waste streams, with the exception of recycling which is free pickups for residents. The City of Vancouver – including Burnaby – has limited garbage disposal to a biweekly pickup schedule, while maintaining their weekly organics and recycling pickups. Universities have introduced a number of educational programs on campuses to encourage students to take an active role in waste management on campus. The new model proposes offering a discount to buildings that have higher waste diversion rates, based on the size of the bins of different streams of waste. In order to effectively introduce this strategy, more metrics should be measured in monthly waste audits. The introduction of barcodes on waste disposal bins should allow for measures of each waste stream to be simple and inexpensive, as only scanning and tracking technology would need to be purchased. As well, there will be an immediate decrease in garbage pickups, inspired by Vancouver and Burnaby reducing the garbage pickups to a biweekly manner. Thirdly, fines for high rates of contamination should be introduced, especially for that of contaminated organics bins. The combination of the above three processes should advance the movement of UBC campus towards zero waste. Moving forwards, it is essential to recognize that the industrial composting machinery is reaching the end of its life. In order to replace the machine, research must be conducted to ensure that UBC purchases the most efficient industrial composter. As well, more educational programming should be rolled out to the primary waste sorters on campus – the students – in order to increase the waste diversion rate and decrease the contamination in all the waste streams. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.794 | 0.669 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".