Lifting the Veil of Ignorance: Prison Cruelty, Sentencing Theory, and the Failure of Liberal Retributivism
Bibliographic record
Abstract
Abstract Criminologists have criticized the gap between retributive theory and prison realities. In this study, we drew on qualitative findings from the Supreme Court judges of Israel to explore how judicial decision-makers construct the relationship between their retributive theory and their vision of prison life. We found that these judges perceived prison to be a disproportionate and cruel punishment. In responding to prison excessiveness, these judges constructed a “veil of ignorance” between the phases of sentencing and imprisonment by (a) re-theorizing retribution; (b) closing the gap between sentencing and prison, and (c) neutralizing responsibility. The findings shed light on the judiciary’s epistemology of prisons and its meaning for their retributive theory. In conclusion, the boundaries of retributive scholarship should be expanded to include more fully the problematic meaning of prison cruelties for judges’ philosophies and consciousness.
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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 | 0.001 | 0.007 |
| 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 | 0.003 |
| 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".