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Record W1987166967 · doi:10.1163/156920806779152291

In Who's Interest? Levirat and Sororat Marriages in Southeastern Turkey

2006· article· en· W1987166967 on OpenAlexafffund
Aysan Sev’er, Mazhar Bağlı

Bibliographic record

VenueHawwa · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaDicle Üniversitesi
KeywordsSisterWifeVetoConfusionPower (physics)BrotherSame sexPsychologyGender studiesSociologyCriminologyLawPolitical sciencePoliticsPsychoanalysis

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.292
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes2
Has abstractyes

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