A narrative analysis of the justifications and excuses of serious employee fraud offenders
Bibliographic record
Abstract
Abstract Most fraud research in accounting has focused on controls rather than offenders' subjective experience, meaning that our understanding of motive in fraud (defined as linguistic devices employed to justify, interpret, or excuse actions) remains underexplored. This is particularly the case for employee fraud, which has been largely neglected relative to top management fraud or financial statement fraud. To provide a richer understanding of how fraud offenders make sense of their offending, we interviewed 30 serious employee fraud offenders to better investigate their typal vocabularies of motive. We focus on holistic narrative accounts to provide insights into the common justifications and excuses presented by employee fraud offenders. We develop a taxonomy of narrative constructions based on the explanatory locus of the accounts offered by offenders. We identify three common justifications, (1) inconsequentiality motives, (2) permission motives, and (3) unfair treatment motives, and three common excuses, (4) personal crisis motives, (5) addiction motives, and (6) appeasement motives. We draw implications for researching fraud, organizational control, and ethics in accounting education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".