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Record W2585539124 · doi:10.26522/vp.v13i2.1445

Le détective biblique : Daniel et le débat sur une préhistoire du roman policier

2016· article· fr· W2585539124 on OpenAlexvenueno aff
Rebecca Josephy

Bibliographic record

VenueVoix Plurielles · 2016
Typearticle
Languagefr
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Le roman policier est un genre littéraire moderne naissant au dix-neuvième siècle avec la révolution industrielle, d’importants progrès scientifiques et des changements dans la structure des sociétés européennes et nord-américaines. Et pourtant, pour autant que le roman policier fleurit au dix-neuvième siècle et reflète une réalité bien moderne certainement nourrie, voire peut-être déclenchée par de profondes évolutions historiques, il existe bien un exemple lointain et biblique de détective avant la lettre. Daniel, ce sage de la Bible qui démêle des mystères, des puzzles et des casse-tête, exemplifie les qualités les plus caractéristiques du détective. Il recourt à la raison, utilise des situations difficiles à son avantage, lit les personnes au-delà leurs apparences et se fie à l’évidence afin de déterminer leur innocence ou culpabilité.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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