More Than the Sum of Its Parts: A Transformative Theory of Biculturalism
Bibliographic record
Abstract
With the rise of globalization, culture mixing increasingly occurs not only between groups and individuals belonging to different cultures but also within individuals. Biculturals, or people who are part of two cultures, are a growing population that has been studied in recent years; yet, there is still much to learn about exactly how their unique experiences of negotiating their cultures affect the way they think and behave. Past research has at times relied on models of biculturalism that conceptualize biculturals’ characteristics and experiences as simply the sum of their cultures’ influences. Yet, the way biculturals negotiate their cultures may result in unique psychological and social products that go beyond the additive contributions of each culture, suggesting the need for a new transformative theory of biculturalism. In this theoretical contribution, our aims are threefold: to (a) establish the need for a transformative theory of biculturalism, (b) discuss how our new transformative theory unifies existing research on biculturals’ lived experiences, and (c) present novel hypotheses linking specific negotiation processes (i.e., hybridizing, integrating, and frame switching) to unique products within the basic psychological domains of self, motivation, and cognition.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".