Global Partnerships for International Fieldwork in Occupational Therapy: Reflection and Innovation
Bibliographic record
Abstract
International fieldwork placements (IFPs) have become very popular among healthcare students including those in occupational therapy programmes. There are many potential benefits that can accrue to the students; however, there are critiques of international placements especially for students going to underserviced areas. The purpose of this paper is to provide a case study/model programme description that critically reflects on six partnerships in three underserviced countries that provide IFPs to students from one Canadian university. The personal opinions of each partner were collected verbally, by email and by a qualitative review of the past 10 years of partnership interaction. Some of the benefits reported by partners include the development of an increased number of sustainable long-term quality placements, orientation materials, student supports and the involvement of university faculty in research and capacity building projects in partner countries. A number of challenges were identified including the need for an expanded formal agreement, more bilateral feedback and examination of supervision models. This paper examines a limited number of partnerships with only one Canadian partner. Direct input of students is not utilized, although feedback given to co-authors by students is reflected. More research is needed on perspectives of partners in IFPs, impact of IFPs on clinical practice in student's home countries, impact of IFPS on underserviced areas and effective strategies for debriefing.
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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 | 0.033 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".