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Record W2055002938 · doi:10.1177/0894845313481851

Key Relationships for International Student University-to-Work Transitions

2013· article· en· W2055002938 on OpenAlexaff
Natalee Popadiuk, Nancy Arthur

Bibliographic record

VenueJournal of Career Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of CalgaryUniversity of Victoria
Fundersnot available
KeywordsGraduation (instrument)Work (physics)PedagogyCareer developmentPsychologyQualitative researchTransition (genetics)Medical educationSociologyPublic relationsPolitical scienceSocial scienceMedicineEngineering

Abstract

fetched live from OpenAlex

International student research predominantly focuses on the initial and middle stages of their sojourn. Our research, however, specifically addresses how relationships support international students to successfully navigate the late-stage transition from university to work. In this qualitative study, we interviewed 18 international students from diverse cultures, ages, and professions with an emphasis on their last year of university and 3 years post-graduation. We found six major themes: (a) building strong friendships supported the decision to stay, (b) career decision making is a group effort, (c) relationships with supervisors and mentors led to career opportunities, (d) establishing relational networks helped with finding first job, (e) developing connections early in their programs helped in the transition, and (f) mentoring from international alumni would provide role models. We discuss the importance of key relationships for international student success and how relationships are embedded in career decision making. Finally, we provide recommendations for career counselors.

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)0.005
metaresearch head score (Gemma)0.012
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 score0.016
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.005
Scholarly communication0.0090.005
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.065
GPT teacher head0.305
Teacher spread0.240 · 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

Citations67
Published2013
Admission routes1
Has abstractyes

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