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Leisure and Personal Development in an Evangelical Christian Theater Group

2019· article· en· W2970799122 on OpenAlexaff
Marcos Gonçalves Maciel, Paul Heintzman, Ester Rafaela Motta Maciel

Bibliographic record

VenueRevista Subjetividades · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGroup (periodic table)SociologyAestheticsArtReligious studiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

The objective of this study was to investigate whether participation in an evangelical theater group contributes to the personal development of the participants. The choice of venue and participants was intentional and the number of participants was determined according to the technique of data saturation. Responses were examined by the constant comparison technique. There were six participants, three of each sex, with a mean age of 18.2 (± 1.8) years, all unmarried and belonging to the same Evangelical Baptist Church in the city of Belo Horizonte, MG. The main results demonstrate that participants understand leisure as an activity, that participation in the theater group in the evangelical context can be understood as a leisure experience and participation, promotes the development of outcomes related to spirituality, creativity, communication and socialization. We conclude that participation in a theater group in the evangelical context enables leisure experiences and personal development.

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)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.023
GPT teacher head0.315
Teacher spread0.292 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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