Xenophobic and Islamophobic Rhetoric among Evangelical Opinion Leaders in the Age of Trump
Bibliographic record
Abstract
Filled with anti-immigrant and Islamophobic rhetoric and buoyed by overwhelming support from white evangelicals, Donald Trump’s campaign for the presidency shocked the world. Much media coverage and scholarship on Trump’s evangelical support implicitly bought into his populist myth of representing the “legitimate” people who ultimately forced the evangelical elite to come around to their point of view. However, little systematic research has been done investigating whether evangelical leaders changed their rhetoric on immigration and Islam following Trump’s rise to political power or if xenophobic rhetoric was already a feature of evangelical media. To address this question, the author collected a corpus of more than 45,000 articles from prominent online evangelical news Web sites and used text analysis techniques to analyze how evangelical opinion leaders discussed immigration and Islam. Evangelical opinion leaders were already using frames of threat and foreignness in their rhetoric around immigration and Islam even before Trump announced his candidacy for president, and there was little change in this rhetoric following his rise to power. These findings suggest that Trump did not instill xenophobic and Islamophobic views in his followers but instead tapped into ideas that were already prevalent in the evangelical subculture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".