Bibliographic record
Abstract
Many people contributed to this project and deserve recognition, far more than we are able to give here.First, we want to thank the denominational leaders and administrative staff of the Convention Baptist, Christian and Missionary Alliance, Pentecostal Assemblies of Canada, Mennonite Brethren, and Christian Reformed Church who participated in the interviews, promoted our project in their constituencies, and sent us statistics about their denominations.The fifty pastors who provided face-to-face interviews and the 478 pastors who responded to a lengthy telephone interview deserve special thanks.Without their willingness to participate, this book would not exist.We also benefited from the work of Andrew Grenville and Joel Thiessen who completed face-to-face interviews with pastors in Toronto and Calgary, respectively.Advitek, Inc. of Toronto completed the telephone interviews in French and English in a timely and professional manner.Funding for this research came primarily from the Evangelical Fellowship of Canada's Centre for Research on Canadian Evangelicalism, and some findings from our data were published in their online journal, Church & Faith Trends (www.evangelicalfellowship. ca/cft).We could not have completed this project without their generous support, including that of John Stackhouse, Jr, who offered insight and assistance at the beginning of this project.Crandall
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.550 | 0.353 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".