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Record W4318612073 · doi:10.1177/09646639231153134

Re-viewing Video Evidence and Police Violence in the Criminal Courts in Turkey

2023· article· en· W4318612073 on OpenAlexaff
Deniz Pınar Konuk

Bibliographic record

VenueSocial & Legal Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsCarleton University
Fundersnot available
KeywordsImpunityCriminologyTrespassLawLaw enforcementPolitical scienceSociologyPolitics

Abstract

fetched live from OpenAlex

This article offers an analysis of audiovisual evidence claims in the struggle for identifying and documenting police violence in Turkish criminal courts. Focusing on a fatal police shooting in an urban district predominantly populated by leftist groups and marginalized communities, it aims to illustrate the limits of both criminal trials and audiovisual technologies of proof. The “culture of impunity” has been the prevailing framework to describe courts’ denial of the ongoing violence of law enforcement. Instead, this article pays attention to the formation of facts, regulation of sensory perceptions, and affective engagements in the courtroom. Drawing on the ethnographically grounded examination of the hearings and the case file, I argue that criminal trials establish the particular legibility of video evidence and police violence. Furthermore, the breach between the ways of seeing, hearing, and interpreting these media serves to delineate different political communities, challenging the assumed unity over which the law has authority.

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)0.001
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.004
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.135
GPT teacher head0.422
Teacher spread0.287 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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