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Record W560783264

Cultural Criminology: Theories of Crime

2011· book· en· W560783264 on OpenAlexaff
Keith Hayward

Bibliographic record

VenueKent Academic Repository (University of Kent) · 2011
Typebook
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsCriminologyCultural criminologySociologyDeviance (statistics)Green criminologyPublic spaceCriminal justice
DOInot available

Abstract

fetched live from OpenAlex

Cultural criminology has now emerged as a distinct theoretical perspective, and as a notable intellectual alternative to certain aspects of contemporary criminology. Cultural criminology attempts to theorize the interplay of cultural processes, media practices, and crime; the emotional and embodied dimensions of crime and victimization; the particular characteristics of crime within late modern/late capitalist culture; and the role of criminology itself in constructing the reality of crime. In this sense cultural criminology not only offers innovative theoretical models for making sense of crime, criminality, and crime control, but presents as well a critical theory of criminology as a field of study. This collection is designed to highlight each of these dimensions of cultural criminology - its theoretical foundations, its current theoretical trajectories, and its broader theoretical critiques-by presenting the best of cultural criminological work from the United States, Europe, Australia, and elsewhere.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0030.017
Scholarly communication0.0050.006
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.047
GPT teacher head0.271
Teacher spread0.224 · 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 designTheoretical or conceptual
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

Citations10
Published2011
Admission routes1
Has abstractyes

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