Determinants of Arab Public Opinion on Foreign Relations
Bibliographic record
Abstract
Using Zogby International polling data from seven different Arab nations (Egypt, Jordan, Kuwait, Lebanon, Morocco, Saudi Arabia, and the United Arab Emirates) this paper offers a societal-level quantitative analysis (N=91 dyads) of the determinants of Arab public opinion toward 13 different non-Arab countries (Canada, China, France, Germany, India, Iran, Israel, Japan, Pakistan, Russia, Turkey, the United Kingdom, and the United States). We first explore whether Arab public opinion toward these countries is predicted by general “realist,”“liberal,”“Marxist,” and/or “cultural” hypotheses suggested in the IR/foreign policy literature. After finding few statistically significant relationships among these variables, we present evidence that Arab publics evaluate non-Arab countries on the basis of those countries' specific foreign policy behaviors throughout the wider Middle East (e.g., especially those behaviors affecting Palestine and Iraq). Noting that these evaluations occur in the context of competing identity frames, we provisionally link Arab publics' concerns with “regional” matters to the high salience of “Arabist” identity among respondents to the Zogby survey.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".