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Record W2171662470 · doi:10.7202/1009161ar

Sanctions, Censure and Punitive Censorship: Some Targeted Hebrew Translations of Arabic Literature from 1961-1992

2012· article· en· W2171662470 on OpenAlexvenueno aff
Hannah Amit-Kochavi

Bibliographic record

VenueTTR traduction terminologie rédaction · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCensorshipHebrewJudaismApprehensionJewish stateLiteratureSanctionsPoliticsPunitive damagesHebrew BiblePolitical scienceLawHistoryArtPhilosophyBiblical studies

Abstract

fetched live from OpenAlex

Translations of Arabic literature into Hebrew have been marginally present in Israeli Jewish culture for the last 62 years. Their production and reception have been affected by the ongoing political Jewish-Arab conflict which depicts the Arab as a threatening enemy and inferior to the Jew. This depiction has often led to fear and apprehension of Arabic literary works. The present paper focuses on several cases where Hebrew translations of Arabic prose and poetry were publicly condemned as a potential threat to the stability of Israeli Jewish sociopolitical creeds and state security. The various sanctions imposed on the texts and their writers (though not on their translators!) by Israeli authorities, the Israeli Hebrew press and public opinion are described and explained. These sanctions were subsequently lifted after Israeli Jewish writers rose up against censure and censorship by raising their voices in protest.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0070.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.079
GPT teacher head0.282
Teacher spread0.203 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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