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Record W3155052741 · doi:10.1002/bsl.2512

Wanting sex and willing to kill: Examining demographic and cognitive characteristics of violent “involuntary celibates”

2021· article· en· W3155052741 on OpenAlexaff
David Williams, Michael Arntfield, Kaleigh Schaal, Jolene Vincent

Bibliographic record

VenueBehavioral Sciences & the Law · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsWestern University
Fundersnot available
KeywordsGrandiosityHomicidePsychologyEntitlement (fair division)CognitionSocial psychologyPerceptionNarrativePoison controlSuicide preventionHuman factors and ergonomicsCriminologyMedicineNarcissismPsychiatry

Abstract

fetched live from OpenAlex

Over the past several years, an online community of self-described "incels," referring to involuntary celibates, has emerged and gained increased public attention. Central to the guiding incel ideology and master narrative are violent misogynistic beliefs and an attitude of entitlement, based on male gender and social positioning, with respect to obtaining desired and often illusory sexual experiences. While violence and hate speech within the incel community are both common, there exists a notable subset of incels who have been willing to act on those violent beliefs through the commission of acts of multiple murder. This study explores the demographic, cognitive, and other characteristics of seven self-identified incels who have attempted and/or successfully completed homicide. The findings suggest that although self-perceptions tend to reflect either grandiosity or self-deprecation, homicidal incels share similar demographic characteristics and dense common clusters of neutralization techniques, cognitive distortions, and criminal thinking errors.

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)0.001
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 score0.338
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.073
GPT teacher head0.338
Teacher spread0.265 · 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

Citations34
Published2021
Admission routes1
Has abstractyes

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