Bibliographic record
Abstract
Food waste is now recognized as a global problem, with roughly one third of the edible parts of food produced for human consumption lost or destroyed, amounting to approximately $1.3 billion per year. Water and energy, as well as raw materials for future use, are but some of the resources affected by wasting food. Food waste also has serious consequences for the environment and public health. Contrary to the belief that food as organic matter decays or evaporates harmlessly in landfills, the anaerobic decomposition of food [p. 643 ↓ ] waste (and other biodegradable waste) in landfills produces several greenhouse gases including methane, a greenhouse gas that is 21 times more potent than carbon dioxide.The occurrence of waste along the supply chain in industrialized countries differs from that in less industrialized ones. Most food waste in less industrialized countries occurs during the upstream stages of the supply chain—in the production, harvesting, distribution, and storage of food. This is arguably the result of managerial, financial, and technical challenges experienced during harvesting, together with storage issues. Industrialized countries, however, experience food losses further downstream, predominantly in the retail and consumer categories (in households) as well as in the restaurant and catering industry. More specifically, studies undertaken in the United Kingdom, Canada, the United States, and Australia, as well as in other industrialized countries, have found that the majority of food waste occurs downstream in the supply chain, from the consumer and the household. Estimates of food waste by consumers per capita vary remarkably between industrialized and less industrialized countries. In Europe and North America, estimates per capita have been found between 95 and 115 kilograms per year, while in Sub-Saharan Africa and South/Southeast Asia, estimates vary between 6 and 11 kilograms per year per capita.This entry first discusses various conceptions of food waste and how it has been measured. It then reviews responses to food waste through governmental action, initiatives adopted by the food industry, and the emergence of nonprofit organizations that implement food rescue programs that distribute food to those in need.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.185 | 0.146 |
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".