An investigation into introducing liquid sweeteners : sustainability project report
Bibliographic record
Abstract
In some of UBC Food Services' locations, dry sweetener portion packets and other sweetening products have been replaced by pumps that dispense liquid sweeteners (LS). The overall impacts of this change on the sustainability of UBC’s operations are evaluated using a triple bottom line assessment. Through online research and contacting key stakeholders through surveys, the economic, social, and environmental differences between the two options were determined. While the price of LS is higher than dry packets, there might be a reduction in consumption due to decreases in waste and theft. Paper waste from dry packets cannot be composted or recycled due to the chemicals in their inks and plastic linings. LS do not produce paper waste; the plastic bottles can be recycled while the pumps are durable enough to be washed and reused often. The LS manufacturer, Monin, is located in the United States so their products need higher carbon emissions to transport compared to the Canadian dry sugar packet manufacturers. Purchasing from a Canadian manufacturer would also have a greater benefit to Canada's economy. Fair Trade and sustainability programs are supported by all the major sweetener manufacturers. The interviewed LOOP Cafe employees stated that they did not find that there was a significant difference in the time or effort required to set up and/or keep up the LS stations compared to dry sugar packet stations. In the consumer survey, more than half of the participants stated that they have taken extra packets to use at home or disposed of unused packets. As a result, LS should be introduced to more UBC Food Services locations in the future and posters should be displayed to raise consumer awareness. 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.”
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".