‘Food is a Right … Nobody Should Be Starving on Our Streets’: Perceptions of Food Bank Usage in a Mid-Sized City in Ontario, Canada
Bibliographic record
Abstract
The purpose of this exploratory descriptive qualitative study was to explore the experiences of people accessing the food bank in a mid-sized city in Ontario, Canada, and to gain their perspectives on more progressive alternatives to the charitable food bank model. We conducted interviews with 11 clients of the local food bank and two interviews with individuals experiencing food insecurity who do not access food banks (n = 13), and analysed these data using thematic analysis. Findings document participants’ perceptions of the barriers to obtaining an adequate income, the key characteristics of and challenges associated with food banks, and proposed alternatives to the existing model. Using our study data, we document how the extant charitable food system engenders human rights violations; consider what would be required to move from a charitable model to a rights-based approach; and describe how food bank and human rights practitioners can promote a human rights framework in Canadian public policymaking. Through a rights-based framework, food provision moves beyond mere benevolence to positive rights; rights requiring legislative action and legal recourse should they be denied. In seeking alternatives to food banks, we conclude that a national strategy, built on a basic income and human rights framework, is needed. The perpetuation of food banks ensures the charitable food model is preserved, and people remain hungry.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".