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Record W2113942249 · doi:10.7202/017359ar

L’homicide conjugal à Montréal, ses raisons, ses conditions et son déroulement

2005· article· en· W2113942249 on OpenAlexaffvenueabout
Maurice Cusson, Raymonde Boisvert

Bibliographic record

VenueCriminologie · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHomicideRomanceCriminologyPsychologyIntimate partnerPeriod (music)Social psychologyHistoryPsychoanalysisSuicide preventionPoison controlDomestic violenceArtMedicineAestheticsMedical emergency

Abstract

fetched live from OpenAlex

Conjugal homicide is a situation where one person murders another person with whom he or she is involved through a matrimonial, quasi-matrimonial or other romantic relationship, the study of this type of homicide is based on the entirety of conjugal murders known to police (77) and committed in different municipalities on the island of Montreal during two time periods, namely 1954 to 1962 and 1985 to 1989. The great majority of these crimes are committed by a man onto a woman. Analyses show that possessiveness — understood to be the desire of one person to exclusively control the other — is by far the reason which leads a man to murder the woman he supposedly loves. However, this desire to possess or control is not in itself sufficient for a man to execute his criminal activity, since a number of conditions must coexist : the woman questions her relationship with the man ; the man may physically strike the woman ; the man has the advantage of greater physical strength; the period of time involved is sufficiently lengthy allowing the crisis to develop and enter its critical phase and finally, the perpetrator succeeds in surpassing the inhibitions which initially impede one from killing another.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.174
GPT teacher head0.398
Teacher spread0.224 · 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

Citations15
Published2005
Admission routes3
Has abstractyes

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