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Record W2192542993 · doi:10.1177/0886260515619172

Characteristics of Homicide-Suicide in Australia: A Comparison With Homicide-Only and Suicide-Only Cases

2015· article· en· W2192542993 on OpenAlexaff
Samara McPhedran, Li Eriksson, Paul Mazerolle, Diego De Leo, Holly Johnson, Richard Wortley

Bibliographic record

VenueJournal of Interpersonal Violence · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversity of Ottawa
FundersAustralian Research CouncilMental Health Commission
KeywordsHomicidePoison controlSuicide preventionSituational ethicsCriminologyHuman factors and ergonomicsPsychologyInjury preventionOccupational safety and healthMedical emergencyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Homicide-suicide represents one of the rarest forms of lethal violence but often precipitates calls to revise social, health, and justice policies. However, there is little empirical information about this type of violence. The current study uses two unique data sets to examine a wide range of individual and situational characteristics of homicide-suicide, with particular emphasis on establishing whether and how homicide-suicide differs from homicide-only and suicide-only. Findings suggest homicide-suicide may have unique characteristics that set it apart from both homicide-only and suicide-only, as well as sharing certain other characteristics with those two types of events.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.339
Teacher spread0.291 · 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 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

Citations53
Published2015
Admission routes1
Has abstractyes

Explore more

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