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Record W2789324397 · doi:10.3968/10119

Dictating the Narrative and Resisting Dictatorships in Saᶜdī’s Novel al-Aᶜẓam

2017· article· en· W2789324397 on OpenAlexvenueno aff
Sami Alkyam

Bibliographic record

VenueStudies in literature and language · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsDictatorDictatorshipAutocracyNarrativeContext (archaeology)Reading (process)ExploitSociologyAestheticsMedia studiesLiteratureLawHistoryPolitical scienceComputer scienceComputer securityPhilosophyArtPoliticsDemocracy

Abstract

fetched live from OpenAlex

This article examines Ibrāhīm Saᶜdī’s novel, al-Aᶜẓam, in the context of dictator novels. I argue that Saᶜdī utilizes the forms and modes of narration to dictate, or tell, a story against dictatorship and resist oppressive domination. The novel, I suggest, marginalizes and parodies the voice of the dictator and centralizes the voice of marginalized characters in the overall narrative structure by utilizing a “dictatorial” form which permits who can and cannot speak. And by assuming the role of a dictator, the novel creates room for maneuver to not only resist closures but also to represent and critique the dissemination and repression of national history under autocratic and repressive powers. The article also shows how writers exploit the reader’s ability to relive the past vicariously through the act of reading to suggest the implicit demythologization of dictators.

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.017
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.003
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 head0.039
GPT teacher head0.374
Teacher spread0.335 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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