Setting standards for credible compliance and law 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
In this paper we examine the setting of optimal legal standards to simultaneously induce parties to invest in care and to motivate law enforcers to detect violators of the law. The strategic interaction between care providers and law enforcers determines the degree of efficiency achieved by the standards. Our principal finding is that some divergence between the marginal benefits and marginal costs of providing care is required to control enforcement costs. Further, the setting of standards may effectively substitute for the setting of fines when penalties for violation are fixed. In particular, maximal fines may be welfare reducing when standards are set optimally. Nous considérons dans cet article la détermination, en information incomplète, de normes légales optimales pour à la fois inciter les citoyens à faire preuve de diligence (prévention) et motiver les agents de la paix à veiller au respect des lois. L'interaction stratégique entre citoyens et agents de la paix détermine l'efficacité des normes choisies. Notre résultat principal est à l'effet qu'un écart entre bénéfices marginaux et coûts marginaux de la diligence est nécessaire afin de réduire les coûts d'application des lois. De plus, les normes peuvent être un substitut aux amendes lorsque les pénalités pour infraction sont fixes. Des amendes maximales peuvent en particulier être contre‐indiquées lorsque les normes sont optimalement déterminées.
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 | 0.001 | 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) | 0.001 | 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