Food insecurity among Toronto Muslim households during COVID and the role of key Muslim charitable institutions
Bibliographic record
Abstract
Food insecurity, which is a growing issue in Canada, affecting one in eight households, has been exacerbated by the COVID-19 pandemic, impacting one in seven households (Tarasuk and Mitchell 2020). Ethnic and racialized communities, particularly Muslim households, are disproportionately affected. This chapter explores the potential of Muslim philanthropy, guided by Islamic food-related principles (Iftar, Fidya, Kaffara, Udhiya, and Aqeeqa), to address food insecurity in Toronto by reimagining them as the 5 Pillars of Sustainable Food Security (5PSFS). As an action research piece, the chapter, using a grounded theory approach with data from interviews of 15 charitable institutions, reveals that while more Muslims are turning to food banks, local charities underutilize the 5PSFS. This chapter underscores the need for a better understanding of the 5PSFS as a sustainable means of addressing local food insecurity and needs, aligning with Islamic ethics, Maqasid, and fostering stewardship.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".