Apology and Remorse in the Last Statements of Death Row Prisoners
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
The role of apology is beginning to receive attention from within the criminal justice system. Research suggests that both victims and offenders can benefit when the offender offers an apology and shows remorse. Less is known, however, about the frequency with which offenders apologize and the content of their apologies. In this study we conducted an exploratory analysis of remorse‐related content in the last statements of inmates on death row in Texas between December 7, 1982 and August 31, 2007. Almost one‐third of the offenders offered an apology, most of which were directed toward the victim’s family. In addition, these apologies were linked with other indications of remorse and sincerity, such as asking for forgiveness and showing empathy. Logistic regression analyses showed that apology was reliably predicted by these remorse‐related variables, but not by demographic variables or variables related to the crime itself. Implications and future research directions are discussed.
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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 | 0.000 |
| 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 it