In Who's Interest? Levirat and Sororat Marriages in Southeastern Turkey
Bibliographic record
Abstract
Abstract Sororat refers to a man's marriage to his deceased wife's sister, and levirat refers to a woman's marriage to her brother-in-law after the death of her husband. This article explores the gendered reactions to tensions and role confusion in these marriages. Forty-five people who were either currently living, or have recently lived in levirat and sororat marriages were interviewed. We observed that family and kin seem to be equally persistent on formulating levirat or sororat types of marriages for widows and widowers. However, men had an ultimate veto power over these arrangements and women did not. Moreover, tensions on women, especially in terms of establishing sexual intimacy with their new partners were traumatic. We argue that material considerations play a primary role on the continuation of these marriages, despite the problems these marriages entail, especially for women.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".