Acculturation, Dialogical Voices and the Construction of the Diasporic Self
Bibliographic record
Abstract
This article argues that various Third World, diasporic communities (e.g. Indian-American, Chinese-Canadian, Turkish-German), settled primarily in Europe and North America, negotiate their cultural identities as citizens of First World countries while retaining a strong identification with the culture of their home country. A dialogical model of acculturation is employed to explain the psychological complexities, contradictions and cultural specificities involved in the experiences of these non-European, diasporic communities. Such a model illustrates how the diasporic identity is shaped by, and linked to, the cultural and political issues of race, gender, colonization and power that are present in the hostland and the homeland. I draw upon Said's memoir Out of Place (1999) to show how a diasporic immigrant's effort to rework the different parts of one's heritage or ethnicity entails an ongoing, dialogical negotiation between the I positions of feeling simultaneously assimilated, separated and marginalized.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.048 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| 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".