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Record W2762294372 · doi:10.5038/1911-9933.11.2.1485

Unpacking the Mind of Evil: A Sociological Perspective on the Role of Intent and Motivations in Genocide

2017· article· en· W2762294372 on OpenAlexvenueno aff
Timothy Williams, Dominik Pfeiffer

Bibliographic record

VenueGenocide Studies and Prevention · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsUnpackingGenocidePerspective (graphical)SociologySociological imaginationCriminologyEpistemologySocial psychologyPsychologySocial sciencePolitical scienceLawPhilosophyArt

Abstract

fetched live from OpenAlex

For quite some time, theories on the role of intent in genocide were conceptually frozen in polarised liberal and post-liberal, or purpose- and knowledge-based approaches, respectively. In accordance with recent criminological thought that moves beyond the narrow debate, this article develops a new sociological perspective on the role of intent in genocide. Drawing on frame analysis it is argued that intent is mainly relevant for framing genocidal action at the macro level. However, individual low-level perpetrators act from a large number of different motivations, of which ideologies of intent are only one. Others range from obedience to authority, coercion and group pressures to sadism, opportunism or the allure of status and power. Further, rethinking genocide with social movement theory helps to combine purpose- and knowledge-based approaches without abandoning a distinct concept of genocide.

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)0.007
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0060.096
Scholarly communication0.0090.012
Open science0.0010.008
Research integrity0.0030.006
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 head0.107
GPT teacher head0.411
Teacher spread0.303 · 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 designTheoretical or conceptual
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

Citations20
Published2017
Admission routes1
Has abstractyes

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