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Record W2408663298 · doi:10.32674/jis.v6i2.366

The Lived Experiences of Canadian-Born and Foreign-Born Chinese Canadian Post-Secondary Students in Northern Ontario

2016· article· en· W2408663298 on OpenAlexaffabout
Fei Wang

Bibliographic record

VenueJournal of International Students · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAcculturationViewpointsEthnic groupForeign bornIdentity (music)PerceptionInterpretative phenomenological analysisSemi-structured interviewInternational educationStudy abroadMeaning (existential)Chinese americansHigher educationPsychologyPedagogyGender studiesSociologyImmigrationQualitative researchSocial sciencePolitical scienceAnthropology

Abstract

fetched live from OpenAlex

This phenomenological study provided an in-depth description of the internal meaning of the lived experiences of Canadian-born and foreign-born Chinese students in Canada and uncovered the differences in their social experiences. The study used semi-structured interviews to allow the participants to express their views on their lives in Northern Ontario, Canada. Four themes emerged: (a) perceptions of ethnic identity; (b) cultural integration; (c) perceptions of academic performance and (d) the effect of Canadian education on career options. The study revealed that Canadian-born Chinese students differed from their foreign-born counterparts in their viewpoints on ethnic identity; their perceptions concerning acculturation; and academic performance. They shared similarities in their views about Canadian and Chinese educational systems, teaching styles, and their career expectations.

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)0.003
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 score0.059
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0240.009
Scholarly communication0.0040.001
Open science0.0020.005
Research integrity0.0010.001
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 head0.023
GPT teacher head0.394
Teacher spread0.371 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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