Employment status, inflation and suicidal behaviour: An analysis of a stratified sample in Italy
Bibliographic record
Abstract
BACKGROUND: There is abundant empirical evidence of a surplus risk of suicide among the unemployed, although few studies have investigated the influence of economic downturns on suicidal behaviours in an employment status-stratified sample. AIMS: We investigated how economic inflation affected suicidal behaviours according to employment status in Italy from 2001 to 2008. METHODS: Data concerning economically active people were provided by the Italian Institute for Statistical Analysis and by the International Monetary Fund. The association between inflation and completed versus attempted suicide with respect to employment status was investigated in every year and quarter-year of the study time frame. We considered three occupational categories: employed, unemployed who were previously employed and unemployed who had never worked. RESULTS: The unemployed are at higher suicide risk than the employed. Among the PE, a significant association between inflation and suicide attempt was found, whereas no association was reported concerning completed suicides. No association was found between completed and attempted suicides among the employed, the NE and inflation. Completed suicide in females is significantly associated with unemployment in every quarter-year. CONCLUSION: The reported vulnerability to suicidal behaviours among the PE as inflation rises underlines the need of effective support strategies for both genders in times of economic downturns.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".