Perceptions of Jewish and Israelis in Italy: Evidence from a Survey Experiment on Political Orientation
Bibliographic record
Abstract
<span class="abs_content">Following the Hamas attacks of October 7, 2023, and the subsequent outbreak of another phase of the Israel-Palestine conflict, the debate on whether criticism of Israel can mask antisemitic prejudice in Western countries has intensified. This study investigates how ideology shapes perceptions of Jews and Israelis in Italy, a context historically marked by right-wing antisemitism and left-wing anti-imperialist critiques. We employ a survey experiment (n=1,119) to measure attitudes toward Jews and Israelis/Israel, to test the pop-theory that posits a "horseshoe" pattern of antisemitism - that is, antisemitic attitudes should be most prevalent at the extremes of the political spectrum and attenuated at more central positions. Contrary to expectations, our findings show no significant convergence of antisemitic attitudes at the ideological extremes. Instead, left-leaning respondents distinguish more clearly between Jews and Israelis, whereas right-leaning respondents conflate the two identities. These results highlight the mechanism that disentangles prejudice from political critique and underscore the moderating effect of ideology in shaping public opinion toward Jewish/Israeli communities.</span><br />
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".