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Record W2316619275 · doi:10.3138/jrpc.7.1.004

Miracles or Love? How Religious Leaders Communicate Trustworthiness through the Web

2004· article· en· W2316619275 on OpenAlexvenueno aff
Stephano Pace

Bibliographic record

VenueJournal of Religion and Popular Culture · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsTrustworthinessThe InternetElement (criminal law)Order (exchange)Convergence (economics)Computer sciencePublic relationsInternet privacyBusinessSociologyWorld Wide WebPolitical scienceLaw

Abstract

fetched live from OpenAlex

A religious organization should communicate trustworthiness by attempting correctly to interpret its message and by recruiting new members. Modern communication involves new means of communication like the Internet, which has become an important medium capable of spreading a complex message to a large audience. Religious movements are a growing social and organizational force that employ modern communication methods and criteria. This paper addresses the convergence of religious communication and the Internet, by focusing on trust, a fundamental element of any type of communication, especially of a religious kind. Two main drivers can elicit trust: capabilities (the skill to realize what is promised) and benevolence (the lack of any opportunistic or egoistic goal). This paper employs the content analysis method to analyze the biographies of religious leaders posted on the their official web-sites, in order to verify the existence of these two trust drivers, i.e., leader’s capabilities and benevolence. The results demonstrate the different stress placed on each.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.277
Teacher spread0.224 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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