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Record W2793908867 · doi:10.1177/009164711704500405

Attachment to Church Congregation: Contributions to Well-Being over and above Social Support

2017· article· en· W2793908867 on OpenAlexaff
Tracy A. Freeze

Bibliographic record

VenueJournal of Psychology and Theology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsCrandall University
Fundersnot available
KeywordsPsychologySocial supportAffect (linguistics)Social psychologyAttachment theory

Abstract

fetched live from OpenAlex

Over the last three decades, research has established a strong link between attachment and well-being as well as social support and well-being. Past research found that attachment to church congregation predicted well-being over and above that predicted by attachment to God. However, it is unknown if attachment to church congregation predicts well-being over and above that predicted by social support. Therefore, the purpose of this study was to determine if attachment to church congregation could explain a portion of the variance in negative affect, positive affect, satisfaction with life, and daily spiritual experiences, beyond that explained by religious social support and perceived social support. The data from 201 participants indicated that religious social support, perceived social support, and attachment to church congregation each predicted different aspects of well-being. Only negative affect was predicted by attachment to church congregation beyond that predicted by social support. More research is needed to better understand the relationship between attachment to church congregation, social support, and well-being.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.439
Teacher spread0.413 · 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 designObservational
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

Citations6
Published2017
Admission routes1
Has abstractyes

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