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Record W7115174734 · doi:10.4000/15ch9

Don’t Try This at Home: Interwar Parodies of Crime Fiction in the Eastern Mediterranean

2025· article· pt· W7115174734 on OpenAlexvenueno aff

Bibliographic record

VenueBelphégor · 2025
Typearticle
Languagept
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)Power (physics)NarrativeDemocracyInterwar periodCorporate governance

Abstract

fetched live from OpenAlex

This article explores the insights that crime fiction offers on state formation and democratic governance in modern Greece and Egypt. Despite differing historical paths after centuries of Ottoman rule, both nations experienced periods of democratic renegotiation alongside advancements in education and the press, which have been identified as factors facilitating the emergence of crime fiction. In the Interwar period, Greek author Nirvanas and Egyptian author al-Ḥakīm vernacularised the globally dominant genre in their works to critique the modern state’s failures, particularly its inability to ensure law and order. Their novels – Nirvanas’s Έγκλημα and al-Ḥakīm’s Yawmiyyāt – utilised parody to challenge the prevailing narrative of the modern state. The analysis suggests examining the role of the educated/effendiyya class, to which both authors belonged, in upholding the state and critiquing its malfunctioning. Ultimately, early works of crime fiction in the Eastern Mediterranean offer a poignant critique of state power and its ability to deliver on its promises.

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)0.007
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 score0.015
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0150.018
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.055
GPT teacher head0.292
Teacher spread0.236 · 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
Published2025
Admission routes1
Has abstractyes

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