Disentangling the indirect links between socioeconomic status and health: The dynamic roles of work stressors and personal control.
Bibliographic record
Abstract
Prior research has documented an indirect link between socioeconomic status (SES) and health, and the goal in this study was to help unravel this phenomenon from a dynamic perspective. The authors hypothesized that SES would be positively related to feelings of personal control and negatively related to perceived work stressors. Drawing on dynamic conceptualizations of these psychosocial factors, they suggest that these psychosocial factors relate to one another over time. Individuals who have higher levels of personal control experience increasingly fewer work stressors over time than do those with lower levels of personal control, and those who experience greater work stressors increasingly perceive less personal control over time than do those with fewer work stressors. Finally, the authors argue that trajectories of personal control and work stressors are associated with the accumulation of health problems over the same period. Their model was tested with 3-wave data (over 4 years) from a nationally representative sample of Canadian employees (N = 3,419). Latent curve modeling provides support for the proposed dynamic model. Conceptual and practical implications are drawn, and suggestions for future research are outlined.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".