Bibliographic record
Abstract
In this article, I consider the degree to which criminal justice interventions may be expected to ameliorate systemic corruption. I distinguish between two ideal types of corrupt actors – conditional cooperators and autonomous defectors – and argue that the prospects of reform through criminal justice are greatly affected by the relative preponderance of each type. When conditional cooperators predominate, the criminal law serves primarily to provide assurance that a perceived social norm is effective, in that the norm is both widely adhered to, and adhered to because people endorse the propriety of that norm. When autonomous defectors predominate, the criminal law serves primarily to deter would-be cheaters by attaching costs, at least in expectation, to cheating. Because patterns of compliance based upon a social norm tend to be self-reinforcing, unlike patterns of compliance motivated by fear of sanction, I argue that the prospects of sustainable reform through criminal justice interventions is likely to depend to a substantial degree upon convincing people to trust social norms rather than rely upon their private judgments of what is in their interest – that is, to become conditional cooperators.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".