Bibliographic record
Abstract
This article explores how empirical and theological lenses can be brought into focus to study pentecostal divine healing practices. The project takes as a case study the healing prayer practices of globally influential pentecostal networks that developed out of the Toronto Blessing of the 1990s: the United States-based Apostolic Network of Global Awakening and the Mozambique-based Iris Ministries. Although science cannot prove or disprove that prayer really results in divine healing, empirical investigations can corroborate or challenge specific claims. Both social scientific and clinical research methods are valuable in assessing perceptions and measurable effects of healing prayer practices. Theological analysis of how prayer is understood and practiced provides an important tool for designing appropriate empirical studies. This project considers the complementary information provided by before-after medical records, survey responses, clinical measurements, and ethnographic follow-up observations and interviews. Because healing prayer is often transacted in the context of social networks, the sociological theory of Godly Love offers a useful model for interpreting study results. This article argues that the widespread perception that prayer results in divine healing has demonstrably real social effects, and in some cases the social interactions involved in healing rituals produce measurable health outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".