Does Economic Insecurity Cause Weight Gain Among Canadian Labor Force Participants?
Bibliographic record
Abstract
The National Population Health Survey (NPHS) suggests that for labor force participants age 25 to 64, the prevalence of self‐reported obesity in Canada has increased from 16 percent in 1998 to 23 percent in 2008. Using six cycles of NPHS data (1998–2009), I explore Canada's obesity dilemma by considering the effect of economic insecurity—measured as the probability of an individual experiencing a severe negative economic shock. As an identification strategy, a fixed effects model is employed to control for unobserved time‐invariant heterogeneity and a set of instruments based on an individual's economic environment are specified in order to isolate causality. Results suggest that for males age 25 to 64, a 1 percent increase in economic insecurity is predicted to increase their body mass index (BMI) by 0.10 points. For females age 25 to 64, the association between economic insecurity and BMI is statistically insignificant at conventional confidence levels.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".