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Record W7028091147

Disentangling the American Christian Right: An Interview with Dr. Christopher Douglas1

2019· other· en· W7028091147 on OpenAlexaboutno aff

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaTSG101Gestational periodPretextFusible alloyDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

"Christopher Douglas is one of the most prominent scholars who has studied the rise of the conservative ChristianRight in the American political arena and the links of this complex movement to American culture. Prof. Douglastaught at the University of Toronto and, for five years, at Furman University, South Carolina before transferring toUniversity of Victoria in 2004. He teaches American literature, particularly contemporary American fiction, religionand 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 interestingand new perspectives that give fresh vitality to the debates about Christian fundamentalism. Prof. Douglas iscommitted 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."

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0460.015
Scholarly communication0.0070.008
Open science0.0020.006
Research integrity0.0080.025
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.248
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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