Single-use plastic packaging in the Canadian food industry: consumer behavior and perceptions
Bibliographic record
Abstract
Abstract Single-use plastic food packaging is a major contributor to the global solid waste problem. Although the food industry is developing strategies to reduce single-use plastic packaging, it needs to better understand consumer awareness and attitudes about the issue. As consumer awareness about single-use plastic waste outpaces private sector practices, this study considered personal motivation factors, government policies, and innovative solutions related to single-use plastic food packaging. This Canada-wide study surveyed 1014 consumers and their willingness to pay premiums for sustainable food packaging alternatives and motivations to reduce single-use plastic waste. Overwhelmingly, most (93.7%) respondents were personally motivated to reduce consumption of single-use plastic food packaging. Canadians were highly motivated to reduce single-use plastic food packaging, but less willing to pay for sustainable alternatives. While environmental concerns were more critical than food safety, Canadians acknowledged that sustainable packaging alternatives were more desirable than outright plastic bag bans, despite not willing to pay for them. Using approaches that consider multiple driving factors on consumer behavior and opinions towards use of single-use plastic food packaging, limitations, recommendations and future research are proposed.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".