Bibliographic record
Abstract
It is now a common refrain among liberals that Christian Right pastors and television pundits have hijacked evangelical Christianity for partisan gain. This book challenges this notion, arguing that the hijacking metaphor paints a fundamentally distorted picture of how evangelical churches have become politicized. The book reveals how the powerful coalition between evangelicals and the Republican Party is not merely a creation of political elites who have framed conservative issues in religious language, but is anchored in the lives of local congregations. Drawing on research at evangelical churches near the U.S. border with Canada, this book compares how American and Canadian evangelicals talk about politics in congregational settings. While Canadian evangelicals share the same theology and conservative moral attitudes as their American counterparts, their politics are quite different. On the U.S. side of the border, political conservatism is woven into the very fabric of everyday religious practice. The book shows how subtle partisan cues emerge in small group interactions as members define how “we Christians” should relate to others in the broader civic arena, while liberals are cast in the role of adversaries. It explains how the most explicit partisan cues come not from clergy but rather from lay opinion leaders who help their less politically engaged peers to link evangelical identity to conservative politics. This book demonstrates how deep the ties remain between political conservatism and evangelical Christianity in America.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.031 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".