Consumers’ perceptions and behavior toward food waste across countries
Bibliographic record
Abstract
Food waste has become a global issue that has received increased attention. Food waste at the household level is a major source of food loss in developed countries. While culture is an important factor shaping people’s behavior, comparison of food waste behaviors across countries and regions are still limited. This study uses primary data covering the US, Canada, the UK, and France to understand and compare consumers’ food waste behaviors. While we found some common drivers for food waste behavior appliable to all countries, such as age, eating away from home, and using expiration dates, we confirmed that consumers behave significantly different across countries. For example, personal factors such as employment status, household size, and environmental concerns are only found significant in certain countries. Similarly, while convenience-driven consumers tend to waste more across countries, only European consumers who are price and advertising conscious tend to increase their food waste frequency. Moreover, many well-known food waste prevention actions, such as making a shopping list, preserving and freezing food, and being willing to consume leftovers, only appear to work in certain countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".