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Record W4394821915 · doi:10.3390/genealogy8020042

The Nepalese Diaspora and Adaptation in the United States

2024· article· en· W4394821915 on OpenAlexaff
Soni Thapa-Oli, Philip Q. Yang

Bibliographic record

VenueGenealogy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsHumber Polytechnic
Fundersnot available
KeywordsDiasporaEthnic groupAdaptation (eye)ImmigrationHomelandPrejudice (legal term)Political scienceGeographyGender studiesSociologyPsychology

Abstract

fetched live from OpenAlex

The Nepalese in the United States of America (USA) are an emerging diasporic community. In spite of the phenomenal growth of the Nepalese diaspora in the USA in the last more than two decades, little is known about this new diasporic community, especially regarding how the Nepalese adapt to American life. This study documents the rapid growth in Nepalese immigration to the USA in the twenty-first century, based on data from the U.S. Department of Homeland Security. Using the data from an online survey, it analyzes the experiences of the Nepalese in cultural adaptation, structural adaptation, marital adaptation, identificational adaptation, and receptional adaptation. The results show that although the Nepalese have become partly assimilated to American culture, they still to a large extent retain their ethnic culture, ethnic association, ethnic identity, and ethnic marital partners, and they have had mixed experiences of prejudice and discrimination. The findings have significant scholarly and practical implications.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0000.001
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 head0.028
GPT teacher head0.306
Teacher spread0.278 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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