Students' attitudes and potential behaviour with regard to whistle blowing as they pass through a modern medical curriculum
Bibliographic record
Abstract
OBJECTIVE: To examine students' attitudes and potential behaviour with regard to whistle blowing as they progress through a modern undergraduate medical curriculum. DESIGN: Cohort design. SETTING: University of Glasgow Medical School. SUBJECTS: A cohort of students entering Glasgow University's new learner-centred, integrated medical curriculum in October 1996. METHODS: Students' pre- and post-Year 1, post-Year 3 and post-Year 5 responses to the whistle blowing vignette of the Ethics in Health Care Instrument (EHCI) were examined quantitatively and qualitatively. Analysis of students' multichoice answers enabled measurement of movement towards professional consensus opinion. Analysis of written justifications helped determine whether their reasoning was consistent with professional consensus and enabled measurement of change in knowledge content and recognition of the values inherent in the vignette. Themes in students' reasoning behind their decisions of whether or not to whistle blow were also identified. RESULTS: There was little improvement in students' performance as they progressed through the curriculum in terms of their proposed behaviour on meeting the whistle blowing scenario. There was also no improvement in the quality of justifications provided. Students' reasoning on whether or not to whistle blow was found to change as the curriculum progressed. CONCLUSIONS: The EHCI has the potential to elicit students' attitudes towards ethical issues at entry to medical school and to measure change as they progress through the curriculum. Students should be encouraged to contemplate dilemmas from all ethical standpoints and consider relevant legal implications. Whistle blowing should be addressed as part of the wider domain of professionalism.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".