Disentangling the American Christian Right: An Interview with Dr. Christopher Douglas | Decifrando a direita cristã norte-americana: uma entrevista com o Prof. Dr. Christopher Douglas
Bibliographic record
Abstract
Christopher Douglas is one of the most prominent scholars who has studied the rise of the conservative Christian Right in the American political arena and the links of this complex movement to American culture. Prof. Douglas taught at the University of Toronto and, for five years, at Furman University, South Carolina before transferring to University of Victoria in 2004. He teaches American literature, particularly contemporary American fiction, religion and literature, multicultural American literature, postmodernism, and the Bible as Literature. In the interview below, Prof. Douglas talks about his research and the idea behind his book “If God Meant to Interfere”, published in 2016; the explanatory concepts of Christian Multiculturalism and Christian Postmodernism; the spread of fake news, conspiracy theories, and alternative facts among Christian fundamentalists; the American political context. Prof. Douglas also offers interesting comments on the current Brazilian situation. His critical insights provide interesting and new perspectives that give fresh vitality to the debates about Christian fundamentalism. Prof. Douglas is committed to “public-scholar engagement” that is, research-based critical writings for non-academic audiences.Links to his public academic activity are inserted throughout the interview.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.015 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".