Incentives for Offender Research Participation Are Both Ethical and Practical
Bibliographic record
Abstract
There is little consistency in policies concerning incentives for offenders to participate in research. With nonoffenders, incentives are routine; in contrast, many jurisdictions and granting agencies prohibit offenders from receiving any external benefits. The reasons for this prohibition are unclear. Consequently, the authors reviewed the ethical and practical concerns with providing incentives to offenders. They conclude that there are no ethical principles that would justify categorically denying incentives for offenders. Research with offenders, however, presents unique practical concerns that need to be considered when determining the magnitude and form of the incentives. In general, the incentives should not be so large as to compel participation of a vulnerable population or to undermine the goals of punishment and deterrence. The authors propose that incentives for offenders should be routinely permitted, provided that they are no larger than the rewards typically available for other socially valued activities (e.g., inmate pay, minimum wage).
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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 | 0.336 | 0.440 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.017 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".