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Record W2309416032 · doi:10.3968/8239

Religious Perspectives in William Faulkner's Novels

2016· article· en· W2309416032 on OpenAlexvenueno aff
Xiamei Peng

Bibliographic record

VenueStudies in literature and language · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsnot available
Fundersnot available
KeywordsLiteratureReading (process)FeelingContext (archaeology)Old TestamentHistoryPhilosophyArtEpistemologyLinguistics

Abstract

fetched live from OpenAlex

William Faulkner, one of the most eminent writers in the world and America as well, is not an easy writer to interpret. In reply to interviewers’ questions about his reading, Faulkner frequently cites the Old Testament as one of his favorite books. This is significant because many of his critics have hinted at the biblical, the legalistic, elements in his work. It is in 1950 when he delivered his famous Nobel Prize address that people began to read his novels in a completely new point of view and consider him an optimistic and religious writer. In an attempt to give readers a comprehensive understanding of Faulkner and his fictions, the author puts Faulkner in the southern religious context, thus having a thorough and more profound understanding of his religious feeling and religious commitment. The present essay probes deeply into the religious perspectives of three of his canonical masterpieces, The Sound and the Fury (1929), Light in August (1932), and Absalom, Absalom! (1936), which are examples of the Biblical influence on Faulkner’s literary thought.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.018
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.292
Teacher spread0.271 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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