Employment Insurance may mitigate impact of unemployment on food security: Analysis on a propensity-score matched sample from the Canadian Income Survey
Bibliographic record
Abstract
Food insecurity, the inadequate access to food due to financial constraints, affects one-sixth of Canadian households, with substantial health implications. We examine the impact of unemployment and the mitigating effect of Employment Insurance (EI) on household food insecurity in Canada. Using the Canadian Income Survey 2018-2019, we sampled 28,650 households with adult workers 18-64 years old. We used propensity score matching to pair the 4085 households with unemployed workers with 3390 households with only continuously employed workers on their propensity towards unemployment. Among unemployed households, we also matched 2195 EI recipients with 950 nonrecipients. We applied adjusted logistic regression to the two matched samples. Food insecurity affected 15.1% of the households without unemployed workers and 24.6% of their unemployed counterparts, including 22.2% of EI recipients and 27.5% of nonrecipients. Unemployment was associated with 48% (adjusted odds ratio [aOR] 1.48, 95% confidence interval [CI] 1.32-1.66; 5.67 percentage points) higher likelihood of food insecurity. This association was significant and similar across income levels, full-time and part-time workers, and household compositions. EI receipt was associated with 23% (aOR 0.77, 95% CI 0.66-0.90; 4.02 percentage points) lower likelihood of food insecurity, but this association was only significant among households with lower income, full-time workers, and children under 18. The findings suggest a broad impact of unemployment on working adults' food insecurity and a substantial mitigating effect by EI on select unemployed workers. Making EI more generous and accessible for part-time workers may help alleviate food insecurity.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".