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Record W2571357502 · doi:10.1111/jssr.12281

Trans‐Congregational Triadic Closure: Churchgoers’ Networks Within and Beyond the Pews

2016· article· en· W2571357502 on OpenAlexaff
Markus H. Schafer, Laura Upenieks

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsClosure (psychology)SociologyContext (archaeology)Sociology of religionSocial psychologyPhenomenonEpistemologyPsychologySocial sciencePolitical scienceHistoryPhilosophyLaw

Abstract

fetched live from OpenAlex

Triadic closure is the common tendency for connections to emerge between people's social network ties. This phenomenon has clear implications for congregational networks and may underlie many of the social benefits associated with church involvement. Less documented in the sociology of religion, however, is the occurrence of triadic closure involving congregational and noncongregational relationships within people's close personal networks. To conceptualize this boundary‐spanning network overlap, we elaborate the concept of trans‐congregational triadic closure (TCTC). Using data from the Portraits of American Life Survey—a project that examines both general and congregation‐specific networks of U.S. adults—we consider how religious tradition, macro‐level context, and individual factors predict the occurrence of TCTC in churchgoers’ networks. Findings suggest pronounced differences between evangelicals and mainline Protestants, a considerably lower likelihood of TCTC in densely populated areas, and higher likelihoods of TCTC corresponding with long durations of congregational involvement. We conclude by noting some of the implications of TCTC for the lives of individual believers and for religious organizations, and suggest ways that this concept could elucidate further aspects of contemporary religious life.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.057
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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.

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

Citations8
Published2016
Admission routes1
Has abstractyes

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