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Record W2800458785 · doi:10.1163/15700682-12341441

Liberal Hermeneutics of the Spectacular in the Study of the New Testament and the Roman Empire

2018· article· en· W2800458785 on OpenAlexaff
Christopher B. Zeichmann

Bibliographic record

VenueMethod & Theory in the Study of Religion · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHermeneuticsDepictionIdeologyScholarshipEmpireNew TestamentSociologyCapitalismPoliticsState (computer science)Status quoLiteraturePhilosophyHistoryAestheticsEpistemologyClassicsLawPolitical scienceArtArchaeology

Abstract

fetched live from OpenAlex

Abstract Since 9/11, there has been a surge in interest in the topic of violence both among scholars of religion and in the humanities more broadly. This article suggests that such works operate with a “hermeneutics of the spectacular” that functions to legitimate the liberal status quo by concentrating its focus upon the most visibly heinous forms of state violence under the aegis of a politics of “resistance.” This article uses the New Testament and its depiction of the military as a site for thinking about how folk definitions come to classify certain activities as “violent” and not others, both today and in antiquity. If biblical scholarship—or the study of religion more broadly—is to be something other than an ideological repository for late capitalism, it is necessary to reconsider the issue. This article, by point of contrast, discusses three theoretical approaches to violence that may be useful: Objective-Structural Violence, Symbolic Violence, and Violent Subjectivities.

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)0.007
metaresearch head score (Gemma)0.008
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.069
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.003
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 head0.024
GPT teacher head0.373
Teacher spread0.349 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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