The Impact of Athletic Brands on Arab Youth Perceptions of Israel: A Review of Sports Diplomacy in Social Science
Bibliographic record
Abstract
This research offers an Arab view point from the academic fieldwork on the nexus between sports diplomacy and social science. The research examines the impact of sports diplomacy through athletic brands on youth perceptions of Israel in the Arab region. 113 Arab students in four Egyptian and Palestinian Universities were surveyed, through mixed-methods research directed by thematic analysis to examine students’ perceptions of Israel based on the political stance of Arab athletes competing against Israeli athletes at sports mega events. Responses indicate that Arab athletes' conduct towards Israeli counterparts in the realm of sports diplomacy had a significant impact on students' perspectives, predominantly fostering unfavorable impressions of Israel. According to the research, there is a gap between youth opinions and the policies of the respective governments. The research concludes that sports boycott is effective in resisting occupation, and that sports and politics are indivisible as the animosity embedded in the Arab-Israeli conflict reflected on respondents’ preferences and emphasized collective national identity among students in the four universities, that linked competition with Israeli athletes to the perception of Israel as enemy. Therefore, the idea of sports normalization appears to be a myth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".