Street checks and carding: an exploration of a sergeant’s capacity to achieve policy conformance from frontline police officers
Bibliographic record
Abstract
This study aims to fill a void in the extant policy implementation literature that has overlooked the contribution of sergeants to the successful adoption of policy decisions at the frontlines. By focusing on the Regulated Interactions Policy of the Toronto Police Service and adopting a sociological institutionalism perspective, 17 sergeants representing each of the 17 divisions of the Toronto Police Service were interviewed. This research does not aim to assess the efficacy of this policy, but rather, examines its implementation. The findings show that there are a number of perceived internal and external factors that operate to facilitate or hinder a sergeant’s capacity to achieve policy conformance in a police organization in general, and to the Regulated Interactions Policy in particular. Further, these perceived factors are contextualized across the police organization. Prevalent external factors include media portrayals of the police, civilian oversight, perceived levels of respect, and relationship between the police and citizens. Dominant internal factors include supervision, internal discipline, policy and procedure, and top-down command. The findings also demonstrate the methods used by sergeants to positively influence the conformance of frontline officers in a police organization in general, and to the Regulated Interactions Policy in particular. Key methods include communication and translation, rewarding, disciplining, and being present. The findings have three broad implications. First, police officers employ a ‘logic of legitimacy’ to make conformance choices that are perceived to promote individual and organizational legitimacy by improving police relations or avoiding discipline. Second, sergeants achieve conformance from frontline officers by blending the payoffs of an authoritative approach and a supportive approach. Third, the perspective held by police officers of the state of police-citizen interaction is one that is reactive.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".