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Record W4319787527 · doi:10.1080/19438192.2023.2173419

Homeland echoes: music, sound, and devotion among the South Asian Hindu diaspora in Edmonton, Canada

2023· article· en· W4319787527 on OpenAlexaffabout
Subash Giri

Bibliographic record

VenueSouth Asian Diaspora · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiasporaHinduismHomelandPopular musicEthnomusicologySoundscapeSingingMusicalGender studiesPopularitySociologyMedia studiesHistoryVisual artsPolitical scienceReligious studiesArtLawSound (geography)Politics

Abstract

fetched live from OpenAlex

In Edmonton, the capital city of the province of Alberta, Canada, music, sound, and devotion have gained extraordinary popularity and proliferation among the South Asian Hindu diaspora. From festival celebrations to community gatherings or congregations in temples, this phenomenon of Hindu religio-cultural practice has been an important magnet to attract a vast number of the Hindu diaspora. Spending hours together, members of the South Asian Hindu diaspora engage in devotional musical soundscapes; immerse themselves in those soundscapes through clapping, singing, and bodily movements; and deeply engage in devotional activities. Based on the ethnographic fieldwork conducted between 2017 and 2022, including three case studies, this article discusses how these homeland echoes – recreating and resembling homeland music, sound, and devotional practices – play a powerful role in maintaining homeland ties and function as a constitutive element of collective identity of South Asian-ness for the South Asian Hindu diaspora in the Canadian society.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0230.008
Scholarly communication0.0050.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.249
Teacher spread0.229 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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