Determinants of Canadian accounting practitioners' ethical perceptions on earnings management
Bibliographic record
Abstract
The collapses of Enron, WorldCom, and Arthur Andersen have raised a growing concern about earnings management (EM) ethics. These accounting scandals have damaged stakeholders' overall confidence and trust in the accounting profession. The academic community has responded with extensive research into American EM ethics but little is known about Canadian ethical values on perceptions of EM. This project focused on Canadian perspectives and surveyed 175 accounting students from two business schools in British Columbia to determine whether ethical ideologies and individuals' characteristics influence decision-making about EM ethics. Empirical results partially supported hypothesized direct effects for idealism, relativism, Machiavellianism, and locus of control. However, an intriguing finding is that EM ethics was also inversely related to Machiavellianism this reverse relationship contradicts both hypothesized direction and previous research. This discovery may mitigate the sole negative image of Machiavellianism and render the reverse relationship between Machiavellianism and EM ethics possible and sustainable.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".