“We are similar, but different”: Contextualizing the Religious Identities of Indian and Pakistani Immigrant Groups
Bibliographic record
Abstract
This article explores how Indian and Pakistani immigrant groups from the Bay Area in North California relate to and interact with one another. There is limited research on the role of religion in shaping sentiments of distinctiveness or “groupness” among diasporic Indians and Pakistanis in the UK and North America. Through conducting qualitative interviews with 18 Indian and Pakistani immigrants in the Bay Area, I recognized three factors pertaining to religion that were salient in influencing notions of groupness—notions of modernity, sociopolitical factors, and rituals. With respect to these three variables, I flesh out the spectrum of associated groupness; while some factors were linked with high levels of groupness, others enabled the immigrant groups to find commonality with one another. This research is integral to a better understanding of the interactions between South Asians in the diaspora, as well as to gain insight into how these immigrant groups—whose countries of origin share a history of religious conflict—perceive and interact with one another.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".