The chicken or the egg: The reciprocal relationship between job insecurity and mental health complaints
Bibliographic record
Abstract
To push the job insecurity literature forward, we bring together and simultaneously examine multiple theoretical frameworks to explain the direct job insecurity-mental health relationship and the reciprocal mental health-job insecurity relationship. Using 3-wave survey data, with a six-month time lag, from 1994 employees, we found that the stability of job insecurity from Time 1 to Time 2 was positively related to stress and social exchange mechanisms, as well as mental health complaints at Time 3. We also found that the stability of mental health complaints from Time 1 to Time 2 was positively related to the conservation of resources mechanism of absenteeism, as well as to perceptions of job insecurity at Time 3. Moreover, the stability of absenteeism over time was positively related to perceptions of job insecurity at Time 3. We discuss implications for the job insecurity literature, as well as make suggestions for future research and practical implications.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".