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Record W7115815879

A Phenomenographic Study and Critique of Evangelistic Equipping Among Pastors Aligned with the Evangelical Church Movement

2023· article· en· W7115815879 on OpenAlexaff

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTheological Perspectives and Practices
Canadian institutionsMcMaster Divinity College
Fundersnot available
KeywordsEvangelismExpansiveTask (project management)Movement (music)Participant observationPhenomenonChristianityPhenomenography
DOInot available

Abstract

fetched live from OpenAlex

Evangelical churches hold evangelism as a hallmark of their movement, but evangelism and conversion rates are in decline. Might this decline be the result of absent or inadequate evangelistic equipping on the part of the church? This project presents a phenomenographic analysis and critique on how congregations are being equipped for evangelism. It employs both surveys of congregational members as well as pastoral leaders. Follow-up interviews with pastoral leaders have also been used to clarify findings from the initial surveys. These interviews have been analyzed to discover the qualitatively different understandings that are evident in the data regarding the phenomenon of evangelistic equipping. These understandings are categorized, and a description of each category type is provided. The results of these findings provide a more expansive understanding of the equipping task and offer specific ways in which the task of evangelistic equipping can be expanded to serve the Evangelical church better.

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)0.019
metaresearch head score (Gemma)0.027
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 score0.029
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0290.033
Scholarly communication0.0100.008
Open science0.0020.006
Research integrity0.0030.005
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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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