Bibliographic record
Abstract
This study explores the impact of gender and marital status on suicide rates in India. It was hypothesized on the basis of established findings elsewhere that suicide rates for those who are married would be lower than for all other marital categories. It was also predicted that with two significant exceptions for all marital categories, male suicide rates would be higher than female rates. The predicted exceptions were for suicides by widows and widowers and for those who were divorced. Because of the traditional stigmatization of widows, it was hypothesized that their suicide rates would be higher than those of widowers. It was also predicted that the social disapproval of divorce in Indian society would result in higher suicide rates for divorced women than for men. Data are official suicide statistics provided by India's National Crime Records Bureau. The results of the study do not confirm the conventional patterns of variations in suicide according to marital status. In accordance with the traditional hypothesis first enunciated by E. Durkheim, married persons are less prone than the unmarried to commit suicide. Sociological studies over the last eighty years have consistently supported Durkheim's theory. The present data reveal that while marriage provides better protection against suicide for Indian women it does not do so for Indian men.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".