Ethical dilemmas experienced by occupational therapy students – the reality
Bibliographic record
Abstract
Background. Ethics training strives to facilitate critical thinking, objective analysis and clinical reasoning skills to equip students with the ability to make an impartial and unbiased decision in different contexts and diverse client populations. This enhances students’ learning experiences. Occupational therapy (OT) students are expected to work in a variety of contexts. They experience many sources of conflict in their fieldwork practice on a daily basis, while at the same time upholding professional values, responsibilities and duties. Objectives. To determine the issues that students face in their fieldwork practice and address these in an ethical manner. Methods. Qualitative research was done among fourth-year OT students by means of an open-ended questionnaire. Results. Three major themes relevant to ethical issues were identified: professional-student relationship; professional boundaries; and disclosure of information and keeping information confidential. Conclusion . The salient themes identified reflect the primary ethical tensions in the international literature from the UK and Canada, but little evidence has been reported from South Africa. Taking cognizance of this, those who are involved in the training of healthcare professionals should incorporate the identified issues in the class discussions. For many students their fieldwork practice may be their first experience with some of the aforementioned issues. Alluding to these in a safe environment (class situation) and equipping the students with a framework of analysis are very important.
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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 | 0.025 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".