Insecure People in Insecure Places: The Influence of Regional Unemployment on Workers’ Reactions to the Threat of Job Loss
Bibliographic record
Abstract
Social comparison theory predicts that unemployment should be less distressing when the experience is widely shared, but does this prediction extend beyond the unemployed to those who are at risk of job loss? Research demonstrates a link between aggregate unemployment and employed individuals’ perceptions of job insecurity; however, less is known about whether the stress associated with these perceptions is shaped by others’ unemployment experiences. We analyze a nationally representative sample of Canadian workers (Canadian Work, Stress, and Health study; N = 3,900) linked to census data and test whether regional unemployment influences the mental health consequences of job insecurity. Multilevel analyses provide more support for the social norm of insecurity hypothesis over the amplified threat hypothesis: the health penalties of job insecurity are weaker for individuals in high-unemployment regions. This contingency is partially explained by the ability of insecure workers in poor labor market contexts to retain psychological resources important for protecting mental health
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".