Bibliographic record
Abstract
This article analyzes the role of the refrigerator in how food becomes waste in socio-material and ethico-cultural practices. The modern food refrigeration technologies and practices have extended food’s useability time. They have transformed ordinary life by allowing households to store ample amounts of fresh food. However, this study suggests that fridges merit more attention not only in terms of reducing food waste, but in efforts to understand how food waste comes into being. This article draws from an analysis of qualitative interviews with ordinary people in Canada and Finland to show that refrigerators are important agents in the moral narrative of food waste: They provide a concrete space where food becomes waste, a justification for food becoming waste, and a material reference point through which people can talk about wider cultural patterns, moral norms, and ordinary ethical dilemmas tied to food waste. Technical devices such as refrigerators do not alone create or solve the problem of food waste, but they are relevant to the ethics of wasting food. Focusing on the fridge helps to show how human and non-human material worlds are entangled and how an overflowing fridge can structure, illustrate, facilitate, and contribute to human ethical conduct related to food waste in a significant way.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.052 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| 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".