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Record W3008429630 · doi:10.5539/ach.v12n1p9

Multicultural Musicscape for National Pride: Performing Arts of East-Asian Diasporas in Hawai‘i before WWI

2020· article· en· W3008429630 on OpenAlexvenueno aff
Heeyoung Choi

Bibliographic record

VenueAsian Culture and History · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsPrideMulticulturalismEthnic groupHomelandMainstreamImmigrationGender studiesThe artsPopulationSociologyMedia studiesPolitical scienceAnthropologyDemographyLaw

Abstract

fetched live from OpenAlex

This study investigates stage performances of Asian immigrants in the U.S., focusing their cultural interactions in Hawai‘i prior to World War II. Previous studies of Asians in the U.S. during the early twentieth century have focused on their separate ways of preserving homeland culture or presentation of mainstream American culture to express a sense of belonging to the host society and relieve anti-Asian sentiments. Despite increasing cultural interactions in cities during this period, the discussion of cultural exchanges among immigrant communities have received limited attention. This study expands previous perspectives by examining the performing arts to demonstrate that diverse multicultural events in Hawai‘i were important tools to promote respective Asian ethnic groups’ cultural identities, foster interactions among young adults of Asian ancestry, and inspire their national pride. The Asian diasporas in Hawai‘i constituting a majority of the local population, despite foreign-born Asian immigrants’ limited access to U.S. citizenship, appreciated opportunities to curate their own ethnicity on stages and culturally interact with other ethnic groups. The multicultural experiences ultimately instilled the satisfaction and national pride into the young adults of Asian ancestry.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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 teacher head, 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

Citations1
Published2020
Admission routes1
Has abstractyes

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