Preparing Students for an International Career: The Case for Contextualizing and Integrating Ethics Education
Bibliographic record
Abstract
A key aim of IFAC (International Federation of Accountants)’s International Education Standard 4 (IES4) is to raise the ethical awareness of candidates preparing for careers as accounting professionals. This paper reports the results of a survey of undergraduate accounting students at an Australian university, and develops an approach for the implementation of IES4 in business schools with culturally diverse student populations. The survey asks students at different stages of their programs about the contribution of tertiary education to their ethical ideas, drawing conclusions based on their culture, year of study, career intentions, age and gender. It then suggests ways of teaching ethics that value and integrate students’ diverse experiences and cultural backgrounds, as well as their existing knowledge. Such initiatives could expand the horizons of students from all cultural backgrounds by increasing their cultural sensitivity and awareness of ethics as an issue of relevance to their professional careers.
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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 | 0.031 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.035 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.003 | 0.031 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".