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Record W2037377442 · doi:10.1177/000842980603500103

Ironie dramatique dans la mise en intrigue de l'empire en Romains 13, 1-7

2006· article· en· W2037377442 on OpenAlexaffvenue
Robert Hurley

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPrincipateReading (process)PremiseFace (sociological concept)Government (linguistics)LandlordValue (mathematics)PhilosophyLiteratureLawHistoryArtPolitical sciencePoliticsEpistemologyLinguistics

Abstract

fetched live from OpenAlex

Most attempts to explain Romans 13:1-7 proceed from the premise that Paul is speaking plainly and directly as he recommends that Christians adopt a respectful and obedient attitude towards those servants of god, the Roman authorities. Historically, Christians have read the passage as an endorsement of all governmental authority, a conclusion which appears repugnant to most exegetes in the wake of the Shoah and similar government-sponsored atrocities. While some authors explain the passage away by supposing it to be an interpolation, others maintain that it becomes understandable only if one takes into account a very particular set of historical circumstances. Given that elsewhere Paul clearly condemns the lords of the age and their magistrates—most notably for the crucifixion of Jesus and their corrupt practises—a reading of his recommendation in Romans 13 at face value produces insurmountable internal contradictions in the Pauline corpus. When this passage is approached with literary sensibilities, another interpretive option presents itself. The following article proposes an ironic reading of Romans 13:1-7 based on an analysis of a set of internal textual clues (suggested by the theoretical work of Wayne Booth) and supported by recent research into the relations between the nascent church and the oppressive Roman Principate.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.311
Teacher spread0.284 · 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.

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

Citations5
Published2006
Admission routes2
Has abstractyes

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