Acculturation orientations towards Israeli Arabs and Jewish immigrants in Israel
Bibliographic record
Abstract
The State of Israel can be characterized as having two integration policies: an assimilationist one towards “valued” Jewish immigrants and a somewhat ethnist one towards its “devalued” national minority, namely Israeli Arabs. Using the Host Community Acculturation Scale (HCAS), this study explored Jewish undergraduate (N = 153) acculturation orientations towards “valued” Jewish immigrants of Russian and Ethiopian background and towards “devalued” Israeli Arabs. Results showed that Jewish undergraduates mainly endorsed the integrationism and individualism acculturation orientations towards Jewish immigrants. However, they were more segregationist and exclusionist towards Israeli Arabs than towards Jewish immigrants of Russian and Ethiopian background. Assimilation was weakly endorsed towards both Jewish immigrants and Israeli Arabs. Based on an extensive questionnaire, multiple regression analyses showed that each acculturation orientation had a distinct psychological profile. The integrationism and individualism orientations were endorsed by undergraduates who were tolerant towards ethnic diversity, felt secure personally, culturally, and militarily, and did not endorse the social dominance orientation (SDO). In addition to not feeling threatened by the presence of Israeli Arabs, integrationists and individualists were identified as secular Israelis and Labour Party sympathizers rather than as religious Jews. In contrast, the assimilationism, segregationism, and exclusionism orientations were endorsed by undergraduates who felt insecure personally, religiously, culturally, and militarily, who tended to be less tolerant towards ethnic diversity, and who were more prone to endorse the SDO. In addition to feeling threatened by Israeli Arabs, they avoided close relations with Russian and Ethiopian immigrants. Segregationists and exclusionists were identified mainly as Jewish nationals. Orthodox Jews, and as Likud Party sympathizers. Exclusionists were distinctive in also feeling threatened by the presence Jewish immigrants of Russian and Ethiopian background. While taking into consideration the context of intergroup relations in Israel, results are discussed using the Interactive Acculturation Model (Bourhis, Moïse, Perreault, & Senecal, 1997).
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".