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Record W4251919644 · doi:10.3138/gsp.7.1.56

Macro, Meso, and Micro Research on Genocide: Gains, Shortcomings, and Future Areas of Inquiry

2012· article· en· W4251919644 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenocide Studies and Prevention · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideMacroMacro levelEpistemologySociologyPsychologyPolitical sciencePhilosophyComputer scienceEconomicsLaw

Abstract

fetched live from OpenAlex

The article critically reviews the existing literature on genocide and mass violence and divides it according to different levels of analysis: macro, meso, and micro levels.We discuss the main theories and findings at each level of analysis and suggest avenues for further research.We argue that the literature on genocide should pay more attention to meso and micro levels of analysis.We also identify a number of other research problems, including conceptualization, selection bias, case comparability, the role of restraint, the question of change over time, and the need to engage in dialogue with the broader social science scholarship on political violence and intrastate conflict.

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.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.211
GPT teacher head0.463
Teacher spread0.253 · 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