Hijacking the Moral Imperative: How Financial Incentives Can Discourage Whistleblower Reporting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SUMMARY Recently, policy makers have focused significant attention on the use of financial rewards as a means of encouraging whistleblower reporting, e.g., the Dodd-Frank Act (U.S. House of Representatives 2010). While such incentives are meant to increase the likelihood that fraud will be reported in a timely manner, the psychological theory of motivational crowding calls this proposition into question. Motivational crowding warns that the application of financial rewards (an extrinsic motivator) can unintentionally hijack a person's moral motivation to “do the right thing” (an intrinsic motivator). Applying this theory, we conducted an experiment and found that, in certain contexts, incentive programs can inhibit whistleblower reporting to a greater extent than had no incentives been offered at all. We discuss the implications of our results for auditors, audit committees, regulators, and others charged with corporate governance. Data Availability: Available from the authors upon request.
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.
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 | 0.051 | 0.600 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it