Technology, Ethics, and the Pandemic: Responses from Key Accounting Actors
Bibliographic record
Abstract
ABSTRACT A pandemic is an exceptional context involving radical disruptions for organizations and society. Ethical considerations evolve among individuals and organizations, and the way technology is used is an important factor in this evolution. We explore how key actors in the accounting space—namely, the Big 4 firms, the professional accounting associations, and the audit regulators—responded to the conjunction of the pandemic, ethics, and technology. We contextualize our documentation analysis referring to the ETHOs framework, which integrates ethics and technology. Findings suggest that ethics and technology are significant for the professional accounting associations and the audit regulators during the pandemic. In contrast, the Big 4 appear to overlook this importance, focusing instead on gains to be obtained from technology, applying a commercial logic above a professional logic. Our study underscores the importance of considering ethics in the future design and utilization of technology to maintain trust in the accounting profession. Data Availability: Data are available from the public sources cites in the text.
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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 | 0.036 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".