Bibliographic record
Abstract
BACKGROUND: There are limited empirical data to support the theory of a protective effect of parenthood against suicide, as proposed by Durkheim in 1897. I conducted this study to examine whether there is an association between parity and risk of death from suicide among women. METHODS: The study cohort consisted of 1,292,462 women in Taiwan who had a first live birth between Jan. 1, 1978, and Dec. 31, 1987. The women were followed up from the date of their first birth to Dec. 31, 2007. Their vital status was ascertained by means of linking records with data from a computerized mortality database. Cox proportional hazard regression models were used to estimate hazard ratios of death from suicide associated with parity. RESULTS: There were 2252 deaths from suicide during 32 464 187 person-years of follow-up. Suicide-related mortality was 6.94 per 100,000 person-years. After adjustment for age at first birth, marital status, years of schooling and place of delivery, the adjusted hazard ratio was 0.61 (95% confidence interval [CI] 0.54-0.68) among women with two live births and 0.40 (95% CI 0.35-0.45) among those with three or more live births, compared with women who had one live birth. I observed a significantly decreasing trend in adjusted hazard ratios of suicide with increasing parity. INTERPRETATION: This study provides evidence to support Durkheim's hypothesis that parenthood confers a protective effect against suicide.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".