AN EXPERIMENTAL STUDY OF COMPLIANCE AND LEVERAGE IN AUDITING AND REGULATORY ENFORCEMENT
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
Evidence suggests that individuals often comply with regulations even though the frequency of inspections and audits is low. We report a laboratory experiment based on the dynamic model suggested by Harrington (1988) to explain this puzzle in which participants move between two inspection groups that differ in the probability of inspection and severity of fine. Enforcement leverage arises in the Harrington model from movement between the groups based on previous observed compliance and noncompliance. We find that compliance behavior does not change as sharply as the model predicts. A simple model of bounded rationality explains these deviations from optimal behavior. (JEL C91, Q20, Q28 )
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it