The Spread of Anti‐Islamic Sentiment: A Comparison between the United States and Western Europe
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Bibliographic record
Abstract
Since the 1980s, anti‐Islamic sentiment has grown in both the United States and Western Europe. However, the political and electoral success of anti‐Islamic actors has been asymmetrical between these regions. In most countries in Western Europe, anti‐Islamic sentiment is still contained to the fringes. Conversely, it has become highly influential in decision‐making circles in the United States. In this article we show that the demand for anti‐Islamic sentiment and the rhetorical strategies of anti‐Islamic actors have been similar in both parts of the world, but differ in their organizational strength and opportunity structures. In Western Europe, such sentiments are contained to radical right‐wing parties, activists, and think tanks. In contrast, anti‐Islamic forces in the United States have formed a strong, well‐funded, and organized coalition capable of influencing the White House, most recently through Donald Trump's presidency. Using a supply and demand theoretical framework, we argue that these differing supply‐side organizational and opportunity structures help explain the relative differences in success between the two regions. Related Articles Antwi‐Boateng, Osman. 2017. “The Rise of Pan‐Islamic Terrorism in Africa: A Global Security Challenge.” Politics & Policy 45 (2): 253‐284. https://doi.org/10.1111/polp.12195 Maggio, Jim. 2007. “The Presidential Rhetoric of Terror: The (Re)Creation of Reality Immediately after 9/11.” Politics & Policy 35 (4): 810‐835. https://doi.org/10.1111/j.1747-1346.2007.00085.x Stockemer, Daniel. 2016. “Is the Turnout Function in Democracies and Nondemocracies Alike or Different?” Politics & Policy 44 (5): 889‐915. https://doi.org/10.1111/polp.12174
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it