Towards a Sustainable Coffee Cup Culture: A Comprehensive Framework for Preventing Paper Cup Waste in Toronto, Ontario
Bibliographic record
Abstract
The environmental threats posed by plastic waste are a significant challenge closely connected to unsustainable consumption. The COVID-19 pandemic exacerbated the problem by increasing the demand for and consumption of disposable plastic products. In Toronto, there is an urgent need to prevent pollution stemming from disposable coffee cups. Concerning coffee consumption, this research delves into the nexus of consumer behaviour, business practices, and government policy. This study collected data from a survey of 258 coffee consumers and indepth interviews with coffee retailers and an official from the Toronto municipal government. The combination of quantitative and qualitative data derived from participant responses represents a novel methodological contribution to examining sustainability within coffee culture. The results highlight convenience as the paramount factor influencing widespread and enduring sustainable behaviour. The findings underscore a significant preference for social responsibility and stakeholder collaboration as crucial elements to prevent paper cup waste. This study identifies that fostering sustainability among all stakeholders in Toronto necessitates a multifaceted approach that encourages the use of reusable cups. The implications of this study support a holistic strategy integrating consumer, business, and governmental dimensions. This strategy emphasizes collaborative efforts and stakeholder empowerment to ensure commitment to sustainability before, during, and after pandemics. The practical relevance of this research offers a roadmap for developing best practices, policies, resources, and tools to encourage a sustainable coffee cup culture.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.019 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".