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Food banks, food diversion, and other responses

2025· book-chapter· en· W4414513247 on OpenAlexaboutno aff

Bibliographic record

VenuePolicy Press eBooks · 2025
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsFood insecurityStigma (botany)Variety (cybernetics)Food distributionPoliticsFood stampsDistribution (mathematics)Food security

Abstract

fetched live from OpenAlex

This chapter documents the growth and proliferation of a variety of charitable non-governmental responses to the problems of food insecurity in Canada and the UK. This has been associated with an exponential growth of food banks, food diversion schemes, and other community-based activities such as community gardens and kitchens, children’s feeding programmes, and food distribution to families plans. Each will be defined and examples in Canada and the UK provided. The history of these charitable efforts is documented, as is the role played by labour unions, churches, and other well-meaning advocates. It is shown that all these responses are problematic as they fail to address the economic and political causes of food insecurity. Particular details are provided of further failures associated with charitable responses to food insecurity such as the experience of stigma and degradation by users of food banks and promulgation of the belief that food insecurity is being addressed. The role that the corporate sector plays in creating food insecurity is considered and placed alongside their involvement with these charitable efforts.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.003

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.

Opus teacher head0.048
GPT teacher head0.253
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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