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Record W2343881707 · doi:10.1163/15700747-03801007

After Toronto

2016· article· en· W2343881707 on OpenAlexaboutno aff
Michael J. McClymond

Bibliographic record

VenuePneuma · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCharismaBlessingEvangelismPrayerWorshipSociologyDiversity (politics)Christian ministryVitalityReligious studiesGender studiesHistoryAestheticsPolitical scienceTheologyArtLawAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This essay explores the unity and diversity of global charismatic ministries emerging from the 1990s Toronto Blessing revival, including John and Carol Arnott’s Catch the Fire Ministries (Toronto, Canada), Randy Clark’s Global Awakening (Mechanicsburg, Pennsylvania, USA), and Heidi and Rolland Baker’s Iris Ministries (Pemba, Mozambique). Such practices as bodily healing, verbal evangelism, care for the poor, Bible teaching, exuberant worship, “soaking prayer,” and inner healing are held in common, while each group has some area of functional specialization. The post-Toronto movements thus do not present an archetypal, Weberian “routinization of charisma” or a global dissemination of a single, homogenized approach to Christian ministry. A common element among the groups is an insistence on an individual, inner spiritual renewal that must precede any outer work of service. Effective ministry derives from “intimacy with God.” In their diversity, vitality, and adaptability, these post-Toronto movements offer hope for reviving the worldwide charismatic renewal.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.354
Threshold uncertainty score0.921

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3540.117

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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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.

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
Published2016
Admission routes1
Has abstractyes

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