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Record W1988072846 · doi:10.3138/physio.62.3.261

Examining International Clinical Internships for Canadian Physical Therapy Students from 1997 to 2007

2010· article· en· W1988072846 on OpenAlexaffvenueabout
Elizabeth Crawford, John M. Biggar, Adrienne Leggett, Adrian Huang, Brenda Mori, Stephanie Nixon, Michel D. Landry

Bibliographic record

VenuePhysiotherapy Canada · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsInternshipDestinationsMedical educationMedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

PURPOSE: To describe international clinical internships (ICIs) for Canadian physical therapy (PT) students, explore the experiences of individuals involved in ICIs, and develop recommendations for future ICIs based on these findings. METHODS: This study employed a mixed-methods approach. An online questionnaire surveyed academic coordinators of clinical education (ACCEs, n=14) on the availability, destinations, and number of ICIs from 1997 to 2007. Semi-structured telephone interviews were then conducted with eight PT students, seven ACCEs, and three supervising clinicians to investigate their ICI experiences. Interview transcripts were coded descriptively and thematically using NVivo. RESULTS: ICIs are currently available at 12 of 14 Canadian PT schools. A total of 313 students participated in ICIs in 51 different destination countries from 1997 to 2007. Over this period, increasing numbers of students participated in ICIs and developing countries represented an increasing proportion of ICI destinations. Key themes identified in the interviews were opportunities, challenges, and facilitating factors. CONCLUSIONS: ICIs present unique opportunities for Canadian PT students. Recommendations to enhance the quality of future ICIs are (1) clearly defined objectives for ICIs, (2) additional follow-up post-ICI, and (3) improved record keeping and sharing of information on ICI destination countries and host sites.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.091
GPT teacher head0.452
Teacher spread0.361 · 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 designNot applicable
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

Citations22
Published2010
Admission routes3
Has abstractyes

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