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Record W4405971922 · doi:10.1002/jip.1647

The Killing of Cousins and Siblings‐In‐Law in Korea: A Descriptive Study

2025· article· en· W4405971922 on OpenAlexaff
Leah Shon, Phillip Shon

Bibliographic record

VenueJournal of Investigative Psychology and Offender Profiling · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPsychologySocial psychologyCriminologyDevelopmental psychology

Abstract

fetched live from OpenAlex

ABSTRACT The killing of cousins and siblings‐in‐law has been examined as part of ‘relative killings’ in prior research. However, they have not been disaggregated and examined in their own right. A content analysis of a major Korean newspaper ( Chosun Ilbo ) and sentencing verdicts from regional trial courts of original jurisdiction in Korea was conducted. This paper examines the offence characteristics in cousin and siblings‐in‐law killings. Cousin and siblings‐in‐law killings made up 4% of 682 family homicides. The victims and offenders were primarily men who used edged weapons to kill one another during the course of arguments. Women appeared as offenders and victims in the early period (1948–1962) while they appeared primarily as victims in the latter period (2013–2023). The data suggest a shift in the age structure of victims and putative motivations across time. The average age of victims and offenders increased by 20 years; the character of violence also shifted from confrontational homicides to killings in the context of domestic disputes between relatives' spouses.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.379
Teacher spread0.296 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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