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Record W7135673837

Crime, Culture and the Urban Experience

2023· book· pt· W7135673837 on OpenAlexaff
Keith John Hayward

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2023
Typebook
Languagept
FieldSocial Sciences
TopicDecadence, Literature, and Society
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsModernityContext (archaeology)NarrativePoliticsField (mathematics)Order (exchange)Object (grammar)
DOInot available

Abstract

fetched live from OpenAlex

É com enorme satisfação que apresento aos leitores e leitoras do Brasil Crime, Cultura de Consumo e Vivência Urbana, de Keith Hayward, segundo volume da coleção Criminologia Cultural, que coordeno na emais editora. Este livro está fortemente inserido nas tradição críticas de Criminologia, trazendo uma apreciação das mudanças culturais das últimas décadas com o intuito de contribuir para uma compreensão mais qualificada da questão criminal na modernidade tardia. Hayward apresenta uma análise teórica ambiciosa que consiste em uma abordagem cultural que visa compreender o nexo cidade-crime-criminalização-identidade no contexto de uma cultura de consumo. O livro incorpora uma impressionante variedade de literatura além dos limites da Criminologia tradicional - incluindo estudos urbanos, teoria social e, mais notavelmente, de crítica de arte e arquitetura - em uma abordagem marcadamente multidisciplinar. Isso proporciona uma leitura desafiadora e esclarecedora, com ênfase no impacto da cultura de consumo na experiência urbana vivida e na dinâmica espacial da cidade e, por sua vez, na compreensão da transgressão e da criminalidade.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.025
Scholarly communication0.0120.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.057
GPT teacher head0.320
Teacher spread0.263 · 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 designNot applicable
Domainnot available
GenreOther

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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