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Record W2906093957 · doi:10.32920/ryerson.14648559

Immigrating to Canada for a "Better Life" : A Qualitative Study on First Generation Vietnamese Immigrant Youths in Canada in the Twenty-First Century

2021· preprint· en· W2906093957 on OpenAlexaffabout
Thao T.U. Dang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsVietnameseImmigrationSettlement (finance)Context (archaeology)Qualitative researchPolitical scienceWork (physics)GeographyDemographic economicsGender studiesSocioeconomicsEconomic growthSociologySocial scienceBusinessEngineeringArchaeology

Abstract

fetched live from OpenAlex

Through five in-depth interviews, this research paper examines factors influencing recent Vietnamese immigrant youths' decisions to come to Canada, and their initial settlement experiences upon arrival in the first three years. This study mainly focuses on the context of departure, exploring the youths' every-day interactions with their social surroundings in Vietnam, prior to their arrival in Canada. This study found that Vietnamese immigrant youths immigrate to Canada to obtain a 'better life'. The three main factors influencing their decisions to come are: (a) their interactions with overseas Vietnamese (including relatives and non-relatives), (b) their level of paid and domestic work responsibilities in Vietnam compared to Canada.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.108
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0180.006
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.002
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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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