Bibliographic record
Abstract
Across two studies, we tested whether members of host communities (i.e., locals) can themselves simultaneously maintain their national culture maintenance and adapt toward cultural diversity (i.e., multiculturalism) in their own home country, supporting a bidimensional model of acculturation, or whether these strategies are incompatible, supporting a unidimensional model of acculturation. We modified the Vancouver Index of Acculturation (Multi-VIA) to assess locals’ national culture maintenance and multicultural adaptation within their own home country. Study 1 supported the bidimensionality of the Multi-VIA in an American sample ( n = 218). Moreover, we found an oblique association between locals’ national culture maintenance and multicultural adaptation. In Study 2, we tested the Multi-VIA’s psychometric properties across three continent groups (North America, Europe, and Asia; N = 619). Multiple-group confirmatory factor analysis demonstrated good model fit for the entire sample. Nevertheless, the association between national culture maintenance and multicultural adaptation was orthogonal for Asians and oblique for Americans and Europeans. In addition, national culture maintenance predicted higher levels of locals’ life satisfaction, whereas multicultural adaptation was associated with less acculturative stress and greater intercultural sensitivity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".