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As falas do medo: convergências entre as cidades do Porto e Rio de Janeiro

2012· article· pt· W2131603162 on OpenAlexaff
Ximene Rêgo, Luís Fernandes

Bibliographic record

VenueRevista Brasileira de Ciências Sociais · 2012
Typearticle
Languagept
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Tendo como ponto de partida o enigma do paradoxo da insegurança (a ausência de correspondência na variação entre a taxa de criminalidade e o sentimento de insegurança) é proposta uma reflexão em torno das falas do medo produzidas no Porto e no Rio de Janeiro, onde se desenvolveu trabalho de campo. Nesse sentido, são analisadas dimensões presentes no discurso da (in)segurança: as representações dos lugares tidos como perigosos e a relação que se vai elaborando entre centralidades e espaços intersticiais; a construção de um imaginário povoado de figuras da ameaça; as estratégias securitárias mobilizadas para organizar o quotidiano num espaço público percebido como predatório. As falas e as práticas registadas expressam pontos de contacto nas estratégias a que recorrem para acentuar a "perigosidade" da cidade, sempre mais intensas no Rio de Janeiro, mas igualmente presentes no material produzido a partir do Porto; paralelos que, mais do que a partir das taxas de criminalidade divulgadas ou da experiência direta, se engendram na relação com a cidade - com os seus lugares e os seus atores - permitindo, mesmo num cenário tão desigual, uma aproximação discursiva.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.213
Threshold uncertainty score0.424

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0090.012
Scholarly communication0.0090.003
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.029
GPT teacher head0.328
Teacher spread0.299 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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