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Record W2104248018 · doi:10.1177/096466390000900104

Autonomy, Regulation and the Police Beat

2000· article· en· W2104248018 on OpenAlexaff
Willem de Lint

Bibliographic record

VenueSocial & Legal Studies · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAutonomyDiscretionOfficerSociologyCorporate governanceLawState policePolitical sciencePublic relationsLaw enforcementManagementEconomics

Abstract

fetched live from OpenAlex

In this article, the historical development of the police beat in the context of liberal governance is explored. As a mechanism of surveillance, the beat was a continuation of rules of the nightly watch, characterized by a tight control over watchmen by fixing person, post and time. As a site of police autonomy, the patrol beat facilitated the furtherance of the enterprise of the amateur constabulary and cultivated police officer dominion by matching police authority to territorial imperatives. In this way, discipline and autonomy have been carved into the mobilization of police in an economy or surveillance and discretion. The legacy of night and day patrol offered an initial temporal organization to this economy, with prohibitions and permissions by time and place. Rather than compromising liberal distinctions, this patrol bifurcation allowed their perseverance by structuring police capacity to intervene into the lives of citizens. But while the legacy of liberal autonomy in the police beat has served to maintain police discretion in the short run, technological innovations offering enhanced time and space compression may in the long run threaten that autonomy and, with it, an important grounding of liberal consent policing.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.043
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.062
GPT teacher head0.406
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2000
Admission routes1
Has abstractyes

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