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Record W2983903179 · doi:10.3138/gsi.13.1.07

Cultural Responses to the Anfal and Halabja Massacres

2019· article· en· W2983903179 on OpenAlexvenueno aff
Rebeen Hamarafiq

Bibliographic record

VenueGenocide Studies International · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsTragedy (event)PoliticsPower (physics)Repetition (rhetorical device)Government (linguistics)Media studiesHistoryPolitical scienceLawSociologyLiteratureArtPhilosophyPhysics

Abstract

fetched live from OpenAlex

After the Anfal and Halabja massacres took place inside Kurdistan, Iraq, there was no place for immediate political reaction. For many years, culture took on the role of soothing the tremendous pain everybody was holding while hiding in fear of the Ba’ath regime. Songs were the first medium to represent the tragedy, as images were heavily controlled inside Iraq. Songs were distributed secretly at first, but later the government turned a blind eye to the distribution of many of the songs that were forbidden. After the Kurdish uprising of 1991, a political priority was the opening of the first Kurdish television station. From the very beginning, its programs featured images of both tragedies, which in turn became a permanent part of the station’s broadcasts. These images were so impactful that they were instrumental in the departure of the Saddam regime. Although these images shocked society, they lost their power and became routine from their constant repetition, enforcing public forgetfulness and deeply affecting the entire culture.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.010
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.401
Teacher spread0.356 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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Same venueGenocide Studies InternationalSame topicTurkey's Politics and SocietyFrench-language works237,207