Bibliographic record
Abstract
How has the academy contributed to the horrors of policing in the United States? While many scholars study policing, few do so from a self-reflective position, which would examine how the production of knowledge has often legitimized policing’s harms. As part of a larger effort to encourage researchers to come to terms with the role we have played in facilitating contemporary atrocities, here I reconsider political scientist James Q. Wilson and criminologist George L. Kelling’s 1982 “Broken Windows” essay, as well as its intellectual legacy. Their essay is best known for speculating that police foot-patrols, by cracking down on low-level offenses, will reduce serious crime. While this speculation has become the subject of much public and academic debate, the relationship between policing and crime is only a secondary point in the article. Unfortunately, focusing on this secondary point has led scholarly and public discourse to distort the essay’s arguments. I correct this distortion through a close reading of the essay. Wilson and Kelling argue that the primary objective of the police should be to maintain order rather than to prevent crime or even to enforce the law. As such, police should discourage behavior inconsistent with neighborhood standards (even if it is not criminal) and should also remove “disorderly” people from public life (even if they are not breaking the law). Indeed, Wilson and Kelling actually endorse illegal actions in certain instances: when these actions are committed by either police or vigilantes to fashion and maintain the authoritarian, classist, ableist, and racist order that the authors envision. After discussing how an accurate understanding of the original “Broken Windows” article has the potential to reorient contemporary studies policing, I conclude by locating broken windows theory as an important member of a family of harmful ideas, generated by academics, that have underwritten a wide range of authoritarian policing practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".