“Making” Testimonies: Charismatic Phenomena and Speech Practice in the True Jesus Church of a Southern Fujian County
Bibliographic record
Abstract
Moving beyond the debate on cultural continuity, this article investigates the micro-mechanisms by which charismatic experiences are produced and authenticated in a True Jesus Church (TJC) community in Southern Fujian. Based on ethnographic fieldwork conducted between 2022 and 2024, the study proposes the concept of “making testimonies” to trace the social production of charisma. The analysis identifies three consecutive stages in this mechanism: (1) in everyday interaction, pastoral rhetorical prompting anchors believers’ scattered sensory experiences to church-recognized experiential types; (2) in ritual settings, complex life histories are disciplined into standardized narratives of “grace and conversion” to align with communal identity; and (3) through mediatization, oral accounts are verified, edited, and fixed into an authoritative archive of collective memory. The study argues that these practices are not expressions of “indigenization” but are strategically employed to construct an authenticity that validates the TJC’s theological claim as the “exclusive church of salvation.” By revealing how modern organizational power and media technologies configure the local “landscape of the Spirit,” this research offers a dynamic, practice-oriented framework for understanding Chinese Christianity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".