The Social Production of Food Waste at the Retail-Consumption Interface
Bibliographic record
Abstract
A major problem throughout the world, food waste is an issue that must be addressed not only by all actors in the agri-food chain but also without a silo mentality. To examine this problem, this article considers the interfaces between the stages of the agri-food chain, by emphasizing the interconnectivity of the different links in the chain, and focusing on the interface between retail distribution and consumption. We show that food waste is socially produced through the interactions and practices of the different actors within food systems. The study presented in this article results from a collaboration research project with two organizations involved in the food waste debate. The data analyzed are derived from an online survey of 1026 Quebec consumers and from 14 semi-directed interviews with retail distribution merchants in the Montreal area, Canada. By identifying, describing and analyzing the consumption and commercial and logistical management practices that contribute to food waste, our analysis demonstrates the existence of four symbolic processes that generate food waste at the retail–consumption interface: the economization of waste, the construction of edibility, the construction of freshness, and the moralization of waste. We argue that these processes should be considered when designing solutions to food waste.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| 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".