Needs for food security from the standpoint of Canadian households participating and not participating in community food programmes
Bibliographic record
Abstract
Abstract In a context where food assistance continues to dominate talks on food security, this study was undertaken to refocus the debate on households' needs. Our objective was to examine the food security experience and needs of food‐insecure households from the standpoint of those participating in community programmes for food security as well as those not doing so. Semi‐structured individual interviews were conducted with a purposive sample of 55 food‐insecure households in Quebec City, Canada. Transcriptions were subjected to content analysis. The results revealed distinct food insecurity situations. The interviewees' accounts show that households participating in community food security programmes and non‐participating households did not have the same profile of food insecurity risks and capacity to cope with those risks. Nevertheless, three main categories of needs emerged from all the households: needs specific to food security (particularly good quality diet), needs regarding the conditions necessary for achieving food security (especially financial access to food) and related needs. Food insecurity was seen as involving a cluster of problems. The results reinforce the necessity for responses that are not uniform but rather situation‐specific. Clearly, households are demanding more than food for survival: they need a set of conditions that will ensure them regular and sustainable access to a good quality diet.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".