The influence of environment on the fieldwork experience: Exploring interprofessional student perspectives
Bibliographic record
Abstract
OBJECTIVE: To determine the impact and importance of the physical, social and institutional environments on the outcome of their first fieldwork experience from the perspectives of occupational therapy (OT) and physical therapy (PT) students. PARTICIPANTS: Eighty two percent (n=84) of OT and 65% (n=51) of PT students completed the survey. The majority of students were female, aged 20-25 years, and supervised using a one student to one educator supervision model. METHODS: A paper survey was mailed to all OT and PT students during their junior fieldwork placement. Demographic, nominal score data and responses to closed-ended questions generated descriptive statistics. Qualitative data resulting from the open-ended questions underwent content analysis. RESULTS: OT and PT students' fieldwork experiences and perceptions of their environment were remarkably similar, however, OT students indicated the physical environment (e.g., having a desk, access to a computer) and orientation (e.g., having a tour) were more important to their impressions of the placement as positive. CONCLUSIONS: By knowing how the environment impacts the fieldwork experience for students, stakeholders involved in the fieldwork process are in a better position to identify and be proactive in making changes to improve placement quality.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".