Unemployment and underemployment are causes of suicide
Bibliographic record
Abstract
Epidemiological studies indicate that labor underutilization and suicide are associated, yet it remains unclear whether this association is causal. We applied convergent cross mapping to test for causal effects of unemployment and underemployment on suicidal behavior, using monthly data on labor underutilization and suicide rates in Australia for the period 2004-2016. Our analyses provide evidence that rates of unemployment and underemployment were significant drivers of suicide mortality in Australia over the 13-year study period. Predictive modeling indicates that 9.5% of the ~32,000 suicides reported between 2004 and 2016 resulted directly from labor underutilization, including 1575 suicides attributable to unemployment and 1496 suicides attributable to underemployment. We conclude that economic policies prioritizing full employment should be considered integral to any comprehensive national suicide prevention strategy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".