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TROPA DE CHOQUE E POLÍCIA COMUNITÁRIA: CASAMENTO POSSÍVEL?

2016· article· pt· W2473074080 on OpenAlexaboutno aff
Steevan Oliveira

Bibliographic record

VenueRevista LEVS · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicYouth, Drugs, and Violence
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Resumo: O texto apresenta de forma sucinta os elementos e estratégias gerais que caracterizam o policiamento de proximidade. A partir dessa breve revisão com ênfase na doutrina da Polícia Militar de Minas Gerais, é evidenciada a possibilidade de se adotar os princípios do policiamento comunitário em um campo onde atualmente se predomina as estratégias reativas de polícia: tropa de choque. Para demonstrar a validade dessa argumentação, são apresentadas práticas adotadas pela polícia em Belo Horizonte e em Vancouver, Canadá. Palavras-chave: Polícia de Proximidade; Policiamento Comunitário; Tropa de Choque. Abstract: The text summarily points elements and general aspects that characterize community policing. From this brief review, which emphasizes the doctrine of the Minas Gerais Police, it is evidenced the possibility of adopting the principles of community policing in a field where currently predominates reactive police strategies: riot police. To demonstrate the validity of these arguments, some practices used by police in Belo Horizonte and in Vancouver, Canada, are showed. Key words: Proximity approach; Community Policing; Riot Police.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.244
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0040.008
Scholarly communication0.0080.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.338
Teacher spread0.294 · 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
Published2016
Admission routes1
Has abstractyes

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