Capturing Waste or Capturing Innovation? Comparing Self-Organising Potentials of Surplus Food Redistribution Initiatives to Prevent Food Waste
Why this work is in the frame
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Bibliographic record
Abstract
The context for this article is the rapid international growth of (surplus) food redistribution initiatives. These are frequently reliant on networks of volunteer labour, often coordinated by digital means. Movements with these characteristics are increasingly viewed by researchers, policymakers and practitioners as cases of self-organisation. The article explores the nature and extent of self-organisation in food redistribution initiatives. Two contrasting UK initiatives were studied using ethnographic methods during a period of rapid expansion. The concept of self-organisation was operationalised using three dimensions—autonomy, expansion and governance. One initiative established food banks in close cooperation with corporate food actors. Its franchise charity model involved standardised safety protocols and significant centralised control. The other initiative deliberately pursued autonomy, rapid recruitment and de-centralised governance; nevertheless, collaboration with industry actors and a degree of centralised control became a (contested) part of the approach. We highlight the interplay of organisational agency and institutional structures affecting the self-organisation of surplus food redistribution, including ways in which movement dynamism can involve capture by dominant interests but also the seeds of transformative practices that challenge root causes of food waste, particularly food’s commodification. Our analysis provides a way to compare the potentials of food charity vs mutual aid in effecting systemic change.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it