Bibliographic record
Abstract
This project began in summer of 1995 when I was a doctoral student at the University of Notre Dame.A rusty 1984 Honda Accord took me from Minneapolis to Winnipeg, down to Mississippi, and finally to New Brunswick, where I spent my days interviewing evangelicals and evenings transcribing the interviews from tape.I was impressed by the similarities between active evangelicals in all four locations, and I began to speculate about why those similarities existed.This book, originally my dissertation completed in 1996 , is the result.It is typical of Canadians to understand themselves in contrast to Americans, so as a Canadian sociology student in the US and the son of evangelical missionaries, a comparison of evangelicals in the two countries seemed natural.Regardless of where I travelled, I was warmly received by the people I interviewed.A special thanks to those pastors who gave up valuable time to talk about their faith.They were trusting enough to give a stranger the phone numbers of several of their parishioners and access to their Sunday school classes.I was invited into their homes, greeted at their church services, taken out for meals, and given places to stay, and the personal questions I asked were patiently answered.The whole research process was rewarding because of the kindness and hospitality these people displayed.Since my graduate school days, two research projects that are important to the study of evangelicals in North America have appeared.The first, used extensively in this project, is the 1996 poll "God and Society in North America: A Survey of Religion, Politics and Social
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.565 | 0.378 |
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".