A group-based recidivist sentencing premium? The role of context and cohort effects in the sentencing of terrorist offenders
Bibliographic record
Abstract
Despite recent interest in terrorism little is known about the sentencing of terrorist offenders, and the impact of cohort effects on the sentencing patterns of offenders over the course of a terrorist campaign remains virtually unexplored. The ‘recidivist sentencing premium’ states that offenders who continually engage in criminal activities should be sanctioned more harshly as their careers progress. Unknown, however, is whether a penalty is applied to first time terrorist offenders as a result of the campaign's collective criminal involvement. The current study analyzes changes in the sentencing outcomes of members of the Front de Liberation du Quebec ( n = 108) over the 10 years that the group was active. The findings indicate that context plays a role in both the actions and adjudication of offenders. Cohort effects are uncovered, and offenders sanctioned later in the campaign are generally sentenced more severely than those at the onset for similar offenses.
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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 | 0.002 | 0.001 |
| 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".