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Record W4385956531 · doi:10.5038/1911-9933.17.1.1967

Arts & Literature: Voices of Kurdish Women Survivors: Healing Through Wounds of Genocide

2023· article· en· W4385956531 on OpenAlexvenueno aff
Sarwa Azeez

Bibliographic record

VenueGenocide Studies and Prevention · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsGenocidePoetryAnguishState (computer science)Gender studiesHistoryPsychologySociologyCriminologyLawLiteraturePolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

The Kurdish genocide tragically stole a generation, yet little attention has been given to the profound anguish endured by women left without husbands, fathers or sons. The poems "Alive," "Waiting," “To Hawa,” and "But Then Their Eyes Retained Everything" venture to unveil novel perspectives on the vast expanse of war, violence, trauma, and healing. They explore the impact of Saddam Hussein’s genocide on women during and after the war, its impact on subsequent generations, and the reflections of women on the implications of the Al-Anfal campaign, which spanned from 1986 to 1989. Similarly, the poem "Her Tongue Refuses to Recall," tells the tale of a resilient Yezidi woman who, like thousands of others, was tragically enslaved by the Islamic State, also known as Daesh, during their invasion of Iraqi Kurdistan from 2014 till 2017. By placing women at the forefront instead of the periphery, these poems attempt to enhance our comprehension of how these atrocities have affected families, intimate relationships, and the unique vulnerabilities faced by women.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0170.013
Scholarly communication0.0080.005
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.075
GPT teacher head0.395
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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