The Multicultural Identity Integration Scale (MULTIIS): Developing a comprehensive measure for configuring one’s multiple cultural identities within the self.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The research investigating how one's multiple cultural identities are configured within the self has yet to account for existing cultural identity configurations aside from integration, and for identifying with more than 2 cultural groups at once. The current research addresses these issues by constructing the Multicultural Identity Integration Scale (MULTIIS) to examine 3 different multicultural identity configurations, and their relationship to well-being based on Amiot and colleagues' (2007) cognitive-developmental model of social identity integration (CDSMII). METHOD: Diverse samples of multicultural individuals completed the MULTIIS along with identity and well-being measures. (Study 1A: N = 407; 1B: N = 310; 2A = 338 and 2A = 254) RESULTS: Reliability and confirmatory factorial analyses (Studies 1A and 2A) all supported the factorial structure of the MULTIIS. Regression analyses (Studies 1B and 2B) confirmed that the integration subscale of the MULTIIS positively predicted well-being, whereas compartmentalization negatively predicted well-being. Categorization was inconsistently related to well-being. CONCLUSIONS: These findings support the CDSMII and the usefulness of the MULTIIS measure, and suggest that each identity configuration is uniquely related to well-being outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it