Bibliographic record
Abstract
Inadequate employment, through unemployment or underemployment is expected to have consequences for the health and well-being of Canadians. This dissertation presents three studies centered on the relationship between underemployment and mental health. In the first study, ideal indicators for underemployment are described, and the stress process model is proposed as a theoretical framework for understanding the relationship between underemployment and adverse health outcomes. The second and third studies use data from a community-based survey conducted in London, Ontario, Canada in 1994/5 and 1996/7. Four indicators of underemployment are used including: lower income or benefits than in a previous job, involuntary part-time work, or over-education. The second study tests for the effects of social selection or social causation between psychological distress and employment status using both survey waves. A reciprocal process is found only for unemployment, where elevated psychological distress increases the odds of job loss by the second interview, and losing adequate employment is associated with elevated psychological distress. The transition into or out of underemployment is not associated with psychological distress. The third study focuses on over-education and its association with psychological distress using a stress process model. Potential mediators are tested including chronic strain, financial strain, work-satisfaction, self-esteem, and mastery. Among males, over-education is a significant predictor of elevated psychological distress and lower self-esteem and work satisfaction. For females, over-education is only associated with elevated psychological distress and lower work satisfaction until household income is controlled for. Gender differences are highlighted in this study, demonstrating that males and females experience underemployment differently, and the greater salience of employment status for men’s mental health. In addition, support is found for the stress process model as a framework for investigating the mechanisms that link the experience of employment to adverse health outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".