American Policing at a Crossroads: Unsustainable Policies and The Procedural Justice Alternative
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
As victimization rates have fallen, public preoccupation with policing and its crime-control impact has receded. Terrorism has become the new focal point of concern. But satisfaction with ordinary police practices hides deep problems. The time is therefore ripe for rethinking the assumptions that have guided American police for most of the past two decades. This Article proposes an empirically-grounded shift to what we call a procedural justice model of policing. When law enforcement moves toward this approach, it can be more effective at lower cost and without the negative side effects that currently hamper responses to terrorism and conventional crime. This Article describes the procedural justice model, explains its theoretical and empirical foundations, and discusses its policy implications, both for ordinary policing and for efforts to combat international terrorism.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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