Food capacities and satisfaction in participants in food security community interventions in Montreal, Canada
Bibliographic record
Abstract
Food insecurity is steadily increasing in Canada. The objective of this paper is to determine if food capacities and satisfaction of recently enrolled participants in food security interventions are associated with the intervention having either a traditional or an alternative type of approach. Participants having recently accessed traditional (n = 711) or alternative community interventions (n = 113) in the Montreal metropolitan area, Canada, were interviewed with a questionnaire. The categorizing variable was participation in a community organization providing either traditional interventions, aimed to help people cope with the urgent need of food, or alternative interventions, aimed at first assistance, in addition to the creation of long-term solutions such as social integration and skills development. Participants' food and nutrition-related capacities and food satisfaction are studied. Multilevel regression models were used to assess whether participants took part in a traditional or alternative interventions. These interventions do not reach the same population. Relative to participants in alternative food security interventions, participants in traditional interventions demonstrated less capacity for accessing information about food safety and healthiness, and perceived their diet as less healthy. Traditional food security participants also paid less attention to the nutritional properties of food and reported less satisfaction with quantity, variety and taste of the food they accessed. The reasons why individuals who may benefit the most from alternative interventions were unlikely to participate should be investigated. The potential that food security interventions may inadvertently reinforce social inequalities in health should be considered in future intervention research.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".