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Record W7099578790

VIETNAMESE IN THE UNITED STATES 1. Generations, Immigration and Length of US Residency

2015· article· en· W7099578790 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseImmigrationResentmentQuarter (Canadian coin)PoliticsAcculturation
DOInot available

Abstract

fetched live from OpenAlex

The fall of South Vietnam in 1975 has forever changed the lives of many Vietnamese people and re-sulted in the massive resettlement of hundreds of thousands of families in the United States and world-wide. After almost a quarter of a century of establishment, the Vietnamese community has tremen-dously transformed and adapted to American culture much faster than what people have previously thought of. Unlike other Asian communities whose members immigrated to the United States through employment or family connection, the sudden emergence of the Vietnamese community was perceived as a political downfall of American power, thus resentment towards the Vietnamese was particularly high at times. Many Vietnamese people who first came to the United States in 1975 were mostly from a more affluent or educated social ladder; nevertheless, their struggle to survive in a completely new environment was noted as difficult and painful. In the late 1970s and 1980s, many people risked their lives to flee the country by boats; thus the name “boat people ” was derived from their experience. A majority of people from this second group came from the countryside or fishing villages and perhaps was less formally educated, yet their resettlement was considered easier than that of the first group. They received guid-ance and learned from experience of relatives or friends who had come before them. The third and most

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.046
GPT teacher head0.236
Teacher spread0.191 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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