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Record W4239493414 · doi:10.1017/s0028688511000348

Communities That Write: Christ-Groups, Associations, and Gospel Communities

2012· article· en· W4239493414 on OpenAlexaff
Richard Last

Bibliographic record

VenueNew Testament Studies · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGospelCommon groundScope (computer science)Jesus christHistorical JesusSociologyHistoryEpistemologyLiteraturePhilosophyArtArchaeologyFaithComputer scienceCommunication

Abstract

fetched live from OpenAlex

Critics who posit the ‘gospels for all Christians’ theory contend that gospels reflect neither the history nor the concerns of the communities within which they were produced. Despite advocacy for the theory from an increasing number of scholars, others continue to reconstruct diverse gospel communities. There is some common ground between the two sides of the debate: the majority of scholars from both perspectives agree that gospels were composed within communal settings. If we take this agreement as our starting point and investigate communal writing practices in antiquity, we might productively forge an agreeable method for determining the scope of intended gospel audiences. This study analyzes the collective process of writing in ancient associations, now regarded as analogous in many ways to early Christ-groups. In doing so, a framework is provided for understanding how and to whom gospels produced in Christ-groups might have been composed. The study finds the ‘all Christians’ theory inconsistent with communal practices of writing.

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)0.005
metaresearch head score (Gemma)0.015
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0120.034
Scholarly communication0.0090.008
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.158
GPT teacher head0.312
Teacher spread0.154 · 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

Citations23
Published2012
Admission routes1
Has abstractyes

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