The Pathway Study: Commonalities Across New Food Bank Users in Rural, Suburban and Urban Areas
Bibliographic record
Abstract
Abstract Background Few studies investigate long-term effects of food donation programs on food insecurity, diet, social integration or health. We describe household food insecurity (HFI), health, social integration and sociodemographic characteristics of 1003 new food banks users in rural, suburban and urban areas in Quebec, Canada. Methods Adults requesting food aid for the first time in the past 6 months were recruited in 117 food aid organizations (32 in rural, 35 in suburban, 50 in urban areas) using a nested sampling technique. Baseline data were collected from Sept 2018 to Jan 2020 in computer-assisted face-to-face interviews. Participants will be followed biennially. HFI was assessed with the 18-item Household Food Security Survey Module. Perceived physical and mental health scores were assessed with the SF12V2 module. Psychological distress and social integration were assessed with the Kessler scale K6+ and a modified version of MSPSS Scale. Differences across groups were tested with Chi square, ANOVA and post-hoc tests. Results Most participants reported high levels of materiel deprivation, with some variability across settings. Severe HFI was more prevalent in rural (51%) and urban (47%) areas than in suburbs (38%). More urban participants reported <20000 CAN$/yr (79% vs 74% in suburbs and 69% in rural) although low education level was more prevalent in rural areas (82% reported <12th grade education vs. 67% in suburban and 64% in urban areas). Psychological distress was higher in the suburbs (28%) compared to urban (21%) or rural areas (22%). No differences were detected across settings in social integration or physical or mental health scores. Conclusions New users of food banks report markedly high levels of material, social and health-related deprivation. In-depth analyses will permit more meaningful interpretation of these differences. The Pathways Study will permit better understanding of the life experience of persons requesting food assistance. Key messages People demanding food aid for the first time reported high levels of materiel deprivation, with some variability across settings. Severe housefold insecurity is around 50% among new food aid demanders in rural and urban settings.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".