Becoming Evangelical in Rural Costa Rica: A Study of Religious Conversion and Evangelical Faith and Practice
Bibliographic record
Abstract
Almost daily emotional worship pours from a warehouse-sized evangelical church in the small rural community of Santa Cruz, Costa Rica. Within twenty years an evangelical presence has gone from virtually non-existent to standing alongside the Catholic Church in the area’s religious landscape. Scenarios like this are going on throughout Latin America as evangelical faith has become firmly rooted in the region. In this thesis I provide another ethnographic research context to the growing body of literature focused on Pentecostalism/evangelicalism in Latin America. Like others addressing this dynamic, I explore the factors and motivations that lead people to become evangelical. I approach these questions with particular emphasis on the characteristics of evangelical faith as it is constructed and practiced during church services. Through participant observation during church services and interviews with practicing evangelicals in and around Santa Cruz, I highlight the relationship between the characteristics of an evangelical faith and the factors and motivations that lead people to seek it. To be religiously active in the manner of my informants requires deep commitment and is not a faith adopted and practiced lightly. Those who become evangelical and sustain the demanding practice are likely to seek it for spiritual solutions to difficult life situations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".