The Expressive Value of Prosecuting Aged Defendants: A Rebuke of Ageism
Bibliographic record
Abstract
Abstract A common normative justification for criminal trials is their expressive value. The prosecution of aged defendants, especially those with deteriorating health, seemingly presents new expressive challenges, where the value of judging and punishing past wrongs seems to conflict with sympathies for the elderly, the seeming futility of prosecuting individuals who are unlikely to serve much of a sentence if convicted, and the seeming cruelty of putting the frail/ill through lengthy and taxing trials. Drawing from philosophical literature on respect for persons and the morality of aged-based differential treatment, this paper argues that deciding not to prosecute would be a communicative disservice to the old—defendants, living victims and those left behind, and other aged individuals within a society—by treating the aged as less agentic or as if their past lives and past actions, admirable or detestable, should no longer be associated with them, nor praised or condemned.
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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 | 0.002 |
| 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 | 0.000 |
| 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 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".