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The Classical Origins of Detective Fiction: Sophocles’s Oedipus the King and Ross Macdonald’s The Goodbye Look

2011· article· en· W1814972980 on OpenAlexvenueno aff
Kifah Umari, Fahd A. Salameh, Qusai Al-Thebyan, Nazmi Al-Shalabi

Bibliographic record

VenueCross-cultural communication · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDetective fictionPsycheArtTheme (computing)LiteratureHumanitiesArt historyPhilosophy

Abstract

fetched live from OpenAlex

Macdonald’s presentation of the crime and its detection in The Goodbye Look shows how he finds in detective fiction a logical genre that will enable him to study human motivations and actions in general. Instead of imitating the hard-boiled detective writers who precede him, Macdonald uses the Oedipus theme in this novel to explore the American psyche and to transform detective fiction into a new kind of fiction which is not only about exposing criminals but also about redeeming the innocent. Key words: Classical literature; American literature; American society; American family; Detective fiction; Literature; Fiction; Culture; Psychology Resume Cet article discute la presentation de Macdonald de l'infraction et sa detection dans The Look Goodbye, montre comment il trouve dans le roman policier un genre logiques qui vont lui permettre d'etudier les motivations et des actions humaines en general. Au lieu d'imiter les auteurs de detective durs qui le precedent, Macdonald utilise le theme d'Oedipe dans ce roman pour explorer la psyche americaine et a transformer la fiction policiere dans un nouveau genre de fiction qui n'est pas seulement d'exposer des criminels, mais aussi sur l'echange de l'innocence. Mots cles: Litterature classique; Litterature americaine; La societe Americaine; Famille americaine; Detective de fiction; Litterature, Fiction; Culture; Psychologie

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.003
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.316
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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