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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

2019· article· en· W2995634795 on OpenAlexaboutno aff

Bibliographic record

VenueReflexão · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Political and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismPostmodernismContext (archaeology)PoliticsFundamentalismReligious studiesSociologyAmerican literatureTheologyMedia studiesHistoryLawPolitical sciencePhilosophyArtLiteraturePedagogy

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.022
GPT teacher head0.271
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designNot applicable
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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