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Record W2606628656 · doi:10.3138/gsi.10.2.04

What Could Not Be Written: A Study of the Oral Transmission of Sayfo Genocide Memory Among Assyrians

2016· article· en· W2606628656 on OpenAlexvenueno aff
Naures Atto

Bibliographic record

VenueGenocide Studies International · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsnot available
Fundersnot available
KeywordsGenocidePoetryDiasporaPersecutionHomelandLiteratureHistoryThe HolocaustArtSociologyGender studiesLawPolitical science

Abstract

fetched live from OpenAlex

This article discusses the ways in which eyewitness accounts about the Assyrian Genocide have been transmitted in writing and orally, reconstructed across generations, and how these accounts have been expressed in lamentations, poetry, and songs in the diaspora, after large numbers of Assyrians settled in Western states beginning in the 1960s. The study of poetry and songs is not only important for reasons of literary analysis, but more so because of the relatively few written primary sources about the Assyrian Genocide. The production of poetry and songs has partly been instrumental in avoiding censorship and renewed persecution, but in recent years has additional value as a medium to call for future action in preventing violence and transmiting memories of the past. The article also highlights culturally specific forms of coping with trauma and transmitting memory. It is based on the analysis of Sayfo lamentations and poetry produced in the homeland, 21 Sayfo songs and poems produced in the Western diaspora, and some recent interviews with the writers of these songs.

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)0.003
metaresearch head score (Gemma)0.016
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 score0.013
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0130.009
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0020.003
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 head0.055
GPT teacher head0.359
Teacher spread0.304 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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