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Record W3135953302 · doi:10.15273/jue.v11i1.10866

“We are similar, but different”: Contextualizing the Religious Identities of Indian and Pakistani Immigrant Groups

2021· article· en· W3135953302 on OpenAlexvenueno aff
Ravi Sadhu

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationOptimal distinctiveness theoryDiasporaGender studiesSalientSociologyModernityQualitative researchGeographySocial psychologyAnthropologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.020
Scholarly communication0.0060.005
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.040
GPT teacher head0.328
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueJournal for Undergraduate EthnographySame topicDiaspora, migration, transnational identityFrench-language works237,207