Contextualizing Events in Imagined Communities
Bibliographic record
Abstract
The ongoing denigration of Arabs in the media, the Western democratic political shifts away from Muslim religious freedom, and increasing anxiety about Muslim radicalization prompt the question: How do Arabs respond to global events when the Muslim and Western worlds are perceived to clash? Our study draws on the theory of imagined communities to examine the extent to which exogenous world events influence attitudes towards out-group members in the Egyptian context. We apply a “pre-post” quasi-experimental design using the World Values Survey, and examine the influence the events of September 11 th , 2001 had on Egyptian perceptions of Jews and non-Arabs. Results suggest that intolerance towards both Jews and ethnic minorities decreased after the attacks. Results also suggest a complex, dynamic association between religiosity and tolerance towards out-group members. We conclude by discussing the theoretical contributions of this paper by highlighting the significance of context and religion when framing imagined communities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| 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 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".