Examining International Clinical Internships for Canadian Physical Therapy Students from 1997 to 2007
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".