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Record W1869646826 · doi:10.1002/sem3.20071

Improving Student Success by Understanding Reasons for, Types of, and Appropriate Responses to Stressors Affecting Asian Graduate Students in Canada

2015· article· en· W1869646826 on OpenAlexaffabout
Andrew Kim

Bibliographic record

VenueStrategic Enrollment Management Quarterly · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsStressorPsychologyCoping (psychology)Sociocultural evolutionIntervention (counseling)Academic achievementMedical educationGraduate studentsClinical psychologyDevelopmental psychologyPedagogyMedicinePolitical science

Abstract

fetched live from OpenAlex

An increasing number of university students in Canada are from East Asian countries and enrolled in graduate programs. For these students, unique factors may contribute to a stressful study environment, which in turn can impact academic performance. This article draws on literature to identify five such factors and appropriate coping strategies: (1) occupational factors, (2) sociocultural factors, (3) academic factors, (4) gender, and (5) age. While acknowledging that stressors are complex and can have both additive and subtractive effects on each other, the article recommends several intervention strategies that may be deployed at the institutional level to address and mitigate stress‐related risks to ultimately improve student persistence and success: (1) comprehensive social supports, in which graduate supervisors and peer groups play prominent roles; (2) development of problem‐solving skills early in a student's program, when acculturative and occupational stressors are most severe; and (3) enhanced campus awareness of sociocultural and occupational limits and benefits.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.083
GPT teacher head0.351
Teacher spread0.268 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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