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Record W2130502565 · doi:10.1353/gsp.2012.0003

Genocide Is a Process, Not an Event

2012· article· en· W2130502565 on OpenAlexvenueno aff
Sheri P. Rosenberg

Bibliographic record

VenueGenocide Studies and Prevention · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideMultidisciplinary approachSociologyField (mathematics)Political scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Genocide studies is simultaneously an emerging and accepted category of scholarly inquiry. The field is robust and at a critical turning point as more disciplines engage the subject. This article identifies two areas within the field that suggest the need for further scholarly attention. First, it urges a renewed attention to the processional nature of genocide and the implications that flow from a particularized understanding of it, specifically in relation to prevention. The article explores this relationship by providing a process-oriented examination of the under-theorized concept of "genocide by attrition," seeking engagement and critique of the concept. Second, new disciplines have entered the field of genocide studies, bringing with them new methodologies and insights. While this is a welcome advance, genocide studies must move from multidisciplinary to interdisciplinary research to avoid fragmentation and achieve the diverse objectives of the field.

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)0.008
metaresearch head score (Gemma)0.014
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 score0.011
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0060.046
Scholarly communication0.0110.008
Open science0.0010.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.096
GPT teacher head0.328
Teacher spread0.232 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

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