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Record W2001091633 · doi:10.1108/17596591211192984

Transitional processes culminating in extreme violence

2012· article· en· W2001091633 on OpenAlexaff
Donald G. Dutton

Bibliographic record

VenueJournal of Aggression Conflict and Peace Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAggressionPsychologySocial psychologySituational ethicsCrueltyCriminology

Abstract

fetched live from OpenAlex

Purpose This paper seeks to review transitional processes that foster transitions from non‐aggression to extreme aggression. Most studies on aggression focus either on traits within violent individuals or social contexts that generate violence, less attention has been paid to transitional mechanisms. Design/methodology/approach The paper reviews “long‐term”, i.e. societal transitions that occur prior to and during genocides; mid‐term transitions such as induction into a military or paramilitary societies; and short‐term (situational) transitions that occur in situ . It reviews alterations in emotion, cognition, and behaviour that occur in these transitions and concludes with a description of the generated output behaviours of an extreme and often sadistic nature. Findings The paper concludes with a review of Nell's “Pain‐Blood‐Death” complex as a hypothetical inherited disposition that may be triggered by any or all of these transitional processes leading to cruel aggression. Originality/value The paper raises new concerns about the conceptualizing of extreme violence purely as an outcome of individual pathology and posits instead that a potential for cruelty may be part of our sociobiological heritage as a species. Furthermore, this potential may be tapped into by exposure to toxic war situations resulting in the manifestation of cruel and inhumane treatment of outgroups by soldiers from disparate societies and eras.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.325
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.305
GPT teacher head0.465
Teacher spread0.160 · 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 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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Aggression Conflict and Peace ResearchSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207