Prioritization of the essentials in the spending patterns of Canadian households experiencing food insecurity
Bibliographic record
Abstract
OBJECTIVE: Food insecurity is a potent determinant of health and indicator of material deprivation in many affluent countries. Food insecurity is associated with compromises in food and housing expenditures, but how it relates to other expenditures is unknown. The present study described households' resource allocation over a 12-month period by food insecurity status. DESIGN: Expenditure data from the 2010 Survey of Household Spending were aggregated into four categories (basic needs, other necessities, discretionary, investments/assets) and ten sub-categories (food, clothing, housing, transportation, household/personal care, health/education, leisure, miscellaneous, personal insurance/pension, durables/assets). A four-level food insecurity status was created using the adult-specific items of the Household Food Security Survey Module. Mean dollars spent and budget share by food insecurity status were estimated with generalized linear models adjusted first for household size and composition, and subsequently for after-tax income quartiles. SETTING: Canada. SUBJECTS: Population-based sample of households from the ten provinces (n 9050). RESULTS: Food-secure households had higher mean total expenditures than marginally, moderately and severely food-insecure households (P-trend <0·0001). As severity of food insecurity increased, households spent less on all categories and sub-categories, except transportation, but they allocated a larger budget share to basic needs and smaller shares to discretionary spending and investments/assets. The downward trends for dollars spent on basic needs and other necessities became non-significant after accounting for income, but the upward trend in the budget shares for basic needs persisted. CONCLUSIONS: The spending patterns of food-insecure households suggest that they prioritized essential needs above all else.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".