Becoming ‘Authentic’ Indian women: displacement, home, and identity among women of the Indian diaspora in the USA
Bibliographic record
Abstract
This paper analyzes interviews with 25 immigrant Indian women in the USA, most of whom arrived during the 1980s. Combining data from in-depth interviews of eight of these women from a cultural psychological study and interviews of 17 immigrant Indian women from the Indiana University Oral History Research Center, I use qualitative analysis within the grounded theory approach to offer insights into their lives in the USA. Six themes emerged from their narratives: the move to the USA (‘the shift’) and their feeling of displacement; experiences with religious and racial discrimination; their roles as cultural and national ambassadors for India; employment; marriage; and identity dilemmas. Adding to the literature that eschews hegemonic Western analytical categories to actively consider the perspectives of the participants themselves, I render a nuanced portrayal of the women’s experiences as they actively synthesize a new ‘authentic’ Indianness for themselves and their families while navigating the melancholia of loss, separation, and exclusion.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 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".