Women respondents report higher household food insecurity than do men in similar Canadian households
Bibliographic record
Abstract
OBJECTIVE: We investigated factors accounting for the consistently higher levels of household food insecurity reported by women in Canada. DESIGN: Two cycles of the Canadian Community Health Survey for the years 2005/2006 and 2007/2008 were pooled to examine the association between household food insecurity, measured using the Household Food Security Survey Module and other metrics, and respondent sex. We stratified households as married/cohabiting (in which case, the household respondent was chosen randomly) or non-married (single/widowed/separated/divorced) and adjusted for differences in household characteristics, including the presence of children. SETTING: Canada. SUBJECTS: Analysis was restricted to households dependent on employment/self-employment and whose reported annual household income was below $CAN 100,000. Exclusions included respondents less than 18 years of age, any welfare receipt, and missing food insecurity, marital status, income source and amount, or household composition data. RESULTS: For non-married households, increased food insecurity in female- v. male-led households was accounted for by significant differences in household socio-economic characteristics. In contrast, in married/cohabiting households with or without children, higher food insecurity rates were reported when the respondent was female and neither respondent characteristics nor socio-economic factors accounted for the differences. CONCLUSIONS: Higher rates of food insecurity in non-married households in Canada are largely attributable to women's socio-economic disadvantage. In married households, women appear to report higher levels of food insecurity than men. These findings suggest a possible bias in the measurement of population-level household food insecurity in surveys that do not account for the sex of the respondent in married/cohabiting households.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".