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Record W3117344349 · doi:10.3167/arrs.2020.110105

Weapons for Witnessing

2020· article· en· W3117344349 on OpenAlexaff
Kyle Byron

Bibliographic record

VenueReligion and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRhythmNarrativeExpansiveSermonIdeologyEvangelismDoctrineSociologyAestheticsHistoryLiteratureArtLawPolitical sciencePoliticsArchaeology

Abstract

fetched live from OpenAlex

Drawing on observations of the performances of street preachers in the United States—as well as the texts that inform them—this article explores the concept of rhythm within and beyond the anthropology of religion. More specifically, it develops an expansive concept of rhythm as multiple and interactive, focusing not on a singular rhythm, but on the rhythmic translations that shape the practice of street preaching. First, I argue that the material rhythms of urban infrastructure constrain the narrative rhythms of the street preacher’s sermon, producing a distinct homiletics. I then suggest that the ideological rhythms of war animate the narrative rhythms of the street preacher’s sermon, linking military strategies with tactics of evangelism. Examining the material, narrative, and ideological rhythms of streets, sermons, and military doctrine, this article advances an analytic framework whereby the intersecting rhythmic tensions that shape performance can be registered.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.008
Scholarly communication0.0050.004
Open science0.0010.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0270.004

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 head0.052
GPT teacher head0.340
Teacher spread0.288 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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