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Enablers and challenges to international practice education: a case study

2008· article· en· W2050167521 on OpenAlexaff
Elizabeth Anne Kinsella, Ann Bossers, Donna Ferreira

Bibliographic record

VenueLearning in Health and Social Care · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPracticumPreceptorInternationalizationInternational educationGlobeMedical educationPublic relationsPolitical scienceBusinessMedicineHigher education

Abstract

fetched live from OpenAlex

Abstract Internationalization is a growing priority for professions, universities and governments around the globe. This has led to increased numbers of health and social care students participating in international practice education experiences. This study identifies enablers and challenges to participation in international practicum education through a case study. The case involves one occupational therapy programme and its international partners, and investigates the perspectives of students, university personnel and preceptor stakeholders. Challenges included: lack of financial support, limited placement availability, and procedural complexity. Enablers included: external financial support, champions for the concept, international connections, and access to the appropriate communication technology. Practical insights that may be relevant for enabling student participation in international education experiences are highlighted.

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)0.014
metaresearch head score (Gemma)0.019
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 score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.007
Scholarly communication0.0050.004
Open science0.0020.008
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.234
GPT teacher head0.552
Teacher spread0.318 · 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

Citations39
Published2008
Admission routes1
Has abstractyes

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