Bibliographic record
Abstract
Researchers observed how food providers in the United States and Canada have made changes during the decades of neoliberal policymaking that have seen food banking expand across North America and beyond. These changes, in part, reflect responses to critiques of food banking as an inadequate solution to food insecurity. Food charities have variously attempted to improve provision through healthier procurement, choice-based distribution models, diversified programming, and advocacy for policy solutions. Better food banking, however, does not negate the influence of corporate donors on food charities’ capacity to foster hunger-preventative change, such as the employment practices of those same donors. Meanwhile, grassroots organisers have pushed for systemic solutions to food insecurity and food waste, whether disillusioned volunteers or mutual aid providers. These often operate with far fewer resources than the corporate donors, government agencies, and philanthropists shaping food banking trajectories. Given the barriers to truly doing themselves out of a job, the chapter asks how far such changes address problems of institutionalised emergency food redistribution and what lessons these might yield for UK practitioners and decision-makers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".