The Final Straw : Analyzing waste through the context of the single use plastic ban at York University
Bibliographic record
Abstract
Waste and waste management have become increasingly important issues in the drive towards sustainability and combatting climate change. In this research portfolio, I critically analyze waste and waste management within the context of Canada’s impending national ban on single use plastics. My portfolio contains three separate components: primary research, a theoretical analysis, and reflections on research. \nMy primary research is based on the dialogical aspects of environmental education. I first examine waste and its management at York University using campus waste audit data. Then I use this data to create a survey on York students’ beliefs and behaviours towards single use plastic and composting on campus. I applied the Theory of Planned Behaviour to craft survey questions. The Theory of Planned Behaviour provides a framework for understanding how students’ attitudes, normative beliefs, and perceived behavioural control affect their behaviour. I distributed the web-based survey through This Week @ York, a weekly newsletter that is sent to all students at York University via e-mail. To analyze the survey results, I use a combination of quantitative statistical analyses and qualitative analysis by coding responses thematically. Last, I present environmental education material consisting of infographics and images for social media to equip students to better manage waste on campus. The survey reveals that students have a desire for waste infrastructures but lack an awareness of the existing infrastructures on campus that they desire. These results suggest that environmental education material can be utilized to bridge the gap and communicate to students that York already has some of the infrastructures in place that they seek. My theoretical analysis on waste and waste management considers the concept of waste in the context of neoliberal governmentality and concludes that the responsibility of waste management is increasingly placed on the individual, including the single use plastic ban. This individualization of waste management can be combatted with collective action and stronger regulations that place the responsibility on producers rather than consumers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".