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Record W3143699822 · doi:10.15699/jbibllite.133.4.777

The <em>Testament of Job</em> as an Example of Profeminine Patience Literature

2014· article· en· W3143699822 on OpenAlexaff
Waugh

Bibliographic record

VenueJournal of Biblical Literature · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPatienceRhetoricNew TestamentLiteratureOld TestamentHonorIdentity (music)Power (physics)PhilosophyArtAestheticsTheology

Abstract

fetched live from OpenAlex

Brent D. Shaw, in his very important and influential article “Body/Power/Identity: Passions of the Martyrs,” published in 1996, argues that a new means of self-identification emerges in the late antique period, often denoted by the Greek abstract noun hypomonē (ὑπoμovή, the “endurance of suffering”). The first-century pseudepigraphic text Testament of Job offers evidence for this revaluation of suffering, but Shaw goes on to discover “feminized rhetoric” in this work: a phrase that is too dismissive of the Testament's profeminine content. Feminine rhetoric, despite Shaw's slighting of the idea, is a remarkably precocious feature of the Testament of Job; moreover, the events surrounding the inheritance of Job's three daughters at the end of this text, taken together, probably represent the most explicit example in biblical or apocryphal texts of engagement with what can only be described as feminine language. Not coincidentally, this text also directly fuses ideas of patience with feminine language, so that the Testament of Job and the early passios that feature female protagonists demonstrate the generation of an important tradition (and the generation of a literary genre best called patience literature) in Western culture, where women become famous for patience and endurance just as men can gain honor through exhibiting the traditional manly virtues.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.016
Scholarly communication0.0050.003
Open science0.0010.004
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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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