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Record W2616971039 · doi:10.1162/jinh_a_01090

Genocide and Ethnic Cleansing: Our Global Past

2017· article· en· W2616971039 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Interdisciplinary History · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsGenocideEthnic CleansingEthnic groupCriminologyCrucible (geodemography)Political scienceHistoryThe HolocaustLawSociologyDemography

Abstract

fetched live from OpenAlex

“Genocide” provides a useful optic with which to understand and examine purposeful purges of Mesopotamian, Alexandrine, Visogothic, Norman, Mongol, and Spanish (during the Inquisition) people, and those of more modern times. Raphaël Lemkin’s cross-disciplinary arguments, developed in the crucible of an unfolding Holocaust and trimmed and refined at the United Nations, offer new insights into the actions of rulers and ruling classes, into the elimination or forcible assimilation of all manner of groups, and into the kinds of decisions that dominant populations made throughout recorded time to brand, and then discriminate against and persecute, weaker or minority groups.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.662
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.077
GPT teacher head0.304
Teacher spread0.227 · 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