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Record W2022754007 · doi:10.4102/hts.v70i1.2750

The Letter of Jude and Graeco-Roman Invective

2014· article· en· W2022754007 on OpenAlexaff
Alicia J. Batten

Bibliographic record

VenueHTS Teologiese Studies / Theological Studies · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInvectiveExplicationCharacter (mathematics)Rhetorical questionAdversaryLiteratureArtPhilosophyLawLinguisticsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Many have attempted to identify the opponents in Jude and have addressed the manner in which the author characterises this group. Moreover, scholars have expended considerable energy on the analysis and explication of Jude’s rhetorical structure and style, and there is wide consensus that as a text, Jude is a sophisticated letter. However, less work has attended to the evaluation of Jude within the tradition of Graeco-Roman invective. In comparing verses from Jude to some examples from such literature, we find similar themes. In particular, the letter of Jude and some Graeco-Roman moralists engage in a particular tactic to undermine, even destroy, the character of their opponents. They both present them as effeminates, which, although a stereotype, is one of the worst insults a writer or orator could wage against an adversary. This article argues that Jude engages in such character assassination, invoking effeminacy in the manner that he describes his opponents’ behaviour, and placing them in a long line of debauched and condemned figures from ages past.

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)0.010
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 score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.012
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.081
GPT teacher head0.303
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 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

Citations9
Published2014
Admission routes1
Has abstractyes

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