I Used to Speak in Tongues: Spirituality and Pentecostal Deconversion Narratives
Bibliographic record
Abstract
This dissertation examines Pentecostal deconversion narratives in memoirs byKim Barnes and Dennis Covington, in novels and short stories by Lee Smith, and in promotional interviews with Katy Perry and Megan Fox.They feature protagonists who grow out of Pentecostalism.In most cases, they are young girls who are raised in Pentecostal homes and leave their homes and religions at the same time.In place of Pentecostalism, the protagonists adopt a spirituality that is either liberal or neoliberal.Liberal spirituality encourages experimentation and assimilation of various religious practices and beliefs as long as they complement classic liberal values like individualism, freedom, rationality, pluralism, etc. Neoliberal spirituality is very similar, but it redefines the classic liberal values with a market sensibility so that freedom becomes freedom in the market, and rationality becomes self-interested rationality based on cost/benefit analysis.In most cases, these protagonists' spiritualties fall somewhere on a continuum between liberal and neoliberal extremes.The narratives privilege these spiritualties as more modern, more empowering, and more in keeping with contemporary American values.They also help position the authors as people who are educated, modern, and liberal in their approach to religion.By contrast, the conservative theology and ecstatic religious practices of Pentecostals are represented as oppressive, narrow minded, dogmatic, and most of all, irrational.By extension, Pentecostals themselves are underdeveloped, uneducated, and anachronistic.In fact, while conservative Protestants as a whole occupy an "othered" position in relation to both liberal and neoliberal spirituality, Pentecostalism becomes the epitome of "bad religion" because it embraces ecstatic experiences.iii These narratives serve three compatible purposes: 1) they promote and celebrate liberal and neoliberal approaches to religion; 2) they help establish and solidify a religious/spiritual identity for the author, and by extension, membership within a religious/spiritual community (although it is an amorphous, undefined community); and 3) they provide access to a large "spiritual but not religious" audience, which embraces consumerism.To accomplish all three of these aims, the narratives use Pentecostalism and Pentecostals as a foil, a caricatured other onto which they project exaggerated negative traits.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.031 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".