Bibliographic record
Abstract
This case describes a real-world fraud involving the retail department store Macy’s, a publicly traded company on the NYSE. In late 2024, Macy’s announced that they had discovered an accounting “error” in their financial statements. The discovery of the error forced Macy’s to delay their third quarter earnings release. Macy’s disclosed that a single employee had been falsifying accounting records for approximately three years, leading to financial statement restatements to correct delivery expenses, accruals and related tax effects. The error and restatements led to questions about internal controls at Macy’s. It also leads to questions as to whether this was correctly called an error, or if Macy’s should have described it as a fraud. This case examines the misstatement and its consequences, and can be used in an accounting or auditing classroom to help students understand errors and fraud, internal controls, ethical leadership, and regulatory requirements for publicly traded companies. Students will learn the importance of accuracy, transparency and ethics in record keeping and financial reporting. As we prepare students for the working world, these lessons in ethics will be more important than ever. This case is appropriate for an upper level undergraduate course or a masters level accounting or auditing course.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".