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Record W2549987637 · doi:10.1177/1362480616659814

Cops, cameras, and the policing of ethics

2016· article· en· W2549987637 on OpenAlex
Meg Stalcup, C Hahn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical Criminology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Ottawa
FundersWashington State UniversityArizona State University
KeywordsSubjectivityPragmatismSociologyLaw enforcementField (mathematics)PessimismRelation (database)Police scienceDroneMedia studiesCriminologyLawPolitical scienceComputer scienceEpistemologyCriminal justice

Abstract

fetched live from OpenAlex

In this article, we explore how cameras are used in policing in the United States. We outline the trajectory of key new media technologies, arguing that cameras and social media together generate the ambient surveillance through which graphic violence is now routinely captured and circulated. Drawing on the work of Michel Foucault, we identify and examine intersections between video footage and police subjectivity in case studies of recruit training at the Washington state Basic Law Enforcement Academy and the Seattle Police Department’s body-worn camera project. We analyze these cases in relation to the major arguments for and against initiatives to increase police use of cameras, outlining what we see as techno-optimistic and techno-pessimistic positions. Drawing on the pragmatism of John Dewey, we argue for a third position that calls for field-based inquiry into the specific co-production of socio-techno subjectivities.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.017
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.346
Teacher spread0.288 · 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