Perspectives of directors of civilian oversight of law enforcement agencies
Bibliographic record
Abstract
Purpose The purpose of this paper is to involve interviews with civilian oversight of law enforcement (COLE) directors from throughout the USA with the purpose of obtaining their perspectives on what it takes to create and sustain successful COLE programs. Design/methodology/approach The project involved 24 semi-structured interviews with experienced COLE directors. The interviews were transcribed and coded and this paper presents these perspectives according to patterns identified during analysis. Findings The research identified themes and patterns in the attitudes of the oversight directors which included numerous conditions necessary for success of an oversight agency. Amongst the most important conditions included agency independence, director job security, the need for professional qualified staff, unfettered access to information, the ability to publicly report on the agency’s work and a willingness on the part of government officials to tolerate criticism of the police. Originality/value This is the first study to identify the challenges and impediments to sustainable COLE mechanisms from the point-of-view of experienced agency directors. The findings can be used by future practitioners to learn from past experiences.
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 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".