Policing, Recognition, and the Bind of Legal Cynicism
Bibliographic record
Abstract
Abstract We draw on a unique dataset of 60 semi-structured interviews with recently arrested suspects in Cleveland, Ohio, a city currently under federal consent decree due to police use of excessive force. Through these interviews we shed light on an apparent paradox in research to date—that residents of disadvantaged communities are deeply skeptical about policing, while still believing that the police remain a viable institution for seeking security in their communities. By connecting research on legal cynicism with insights from cultural sociology and the sociology of law, we find that respondents make meaning of this apparent paradox – and the resulting bind in which they find themselves – by stressing the promise of law that underwrites a transformative potential of policing. Through these ideals of legality, residents aspire to material and symbolic forms of recognition from law enforcement, ranging from police presence and safety, to expressions of understanding and feelings of worth. We propose that this desire for broad recognition is central to how suspects make sense of their reliance on police, and we suggest further research into how this struggle for recognition provides a cultural approach for understanding social inequality and its intersection with legality and criminal justice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".