Exploring the Perspectives of Community Mentors in Occupational Therapy Education
Bibliographic record
Abstract
Involving people with disabilities in the education of occupational therapy students is important for improving knowledge, skills, and attitudes that promote client-centered practice. At Queen’s University in Ontario, Canada, community mentors with disabilities are involved in an occupational therapy course designed to enhance student understanding and empathy for the lived experience of disability. With the onset of the COVID-19 pandemic, the course required adjustment to adhere to health and safety precautions. We explored the perspectives of community mentors with disabilities who participated in the course during the pandemic to better understand how pandemic-related restrictions affected the mentoring experience, their relationships with students, and educational quality. Findings revealed that all participants considered their mentor role to be beneficial and positive, regardless of the chosen method of interaction (i.e., in-person or via digital technology). However, mentors with prior experience in this role identified differences in the relational aspects of the experience. Some mentors who had established mentoring patterns pre-pandemic quickly shifted into pre-COVID routines, despite the inherent risk, seemingly based on an internalized image of what the role should entail. Other mentors indicated acceptance of the altered patterns, and noted benefits associated with the use of technology. The findings confirm that ensuring mentor autonomy, providing training to mentors, and continuing to promote the benefits of such a course are crucial to support their role in shaping future occupational therapy practice.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".