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Record W2035453482 · doi:10.1177/030908920302800103

Eliab and the Deuteronomist

2003· article· en· W2035453482 on OpenAlexaff
Keith Bodner

Bibliographic record

VenueJournal for the Study of the Old Testament · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsTyndale University
Fundersnot available
KeywordsNarrativeCharacter (mathematics)PrideLiteraturePhilosophyFace (sociological concept)Value (mathematics)Point (geometry)HistoryArtLinguisticsTheologyComputer scienceMathematics

Abstract

fetched live from OpenAlex

This article is a literary study of Eliab’s characterization and his function within the broader narrative of David. The two scenes where Eliab appears (1 Sam. 16 and 17) need to be read together, since Eliab’s character zone contains a pair of ‘double-voiced’ utterances as defined by Bakhtin: in the first scene of 1 Samuel 16, he is an instrument of correction for the prophet Samuel; in the second scene of 1 Samuel 17, Eliab is used as an instrument of correction for the young David. His words to David in 17.28 are scathing: ‘I know about your pride and the evil of your heart’. A brief survey of secondary literature reveals that most scholars take the words of Eliab at face value, and feel that Eliab must be wrong in his assessment of David’s ‘evil heart’. This study takes a different approach. It is argued here that Eliab’s words are used to sound a warning about the heart of David, a highly complex literary figure. Moreover, since Eliab is used at a very early point in the narrative to inject a note of caution and a foreshadowing of potential flaws surrounding the heart of David, it is surely not coincidental that Eliab’s speech accents reverberate later in the story of David and Bathsheba.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.255
Teacher spread0.221 · 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
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

Citations5
Published2003
Admission routes1
Has abstractyes

Explore more

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