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Práticas insurgentes e contrapoderes no planejamento urbano: o caso de Pointe-Saint-Charles em Montreal

2019· article· pt· W2912865958 on OpenAlexaffabout
Anne Latendresse, Luis Felipe Cunha

Bibliographic record

Venueurbe Revista Brasileira de Gestão Urbana · 2019
Typearticle
Languagept
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesSAINTPolitical scienceArtArt history

Abstract

fetched live from OpenAlex

Resumo Antigo berço da industrialização canadense, Pointe-Saint-Charles é um bairro localizado próximo ao centro da cidade de Montreal, Quebec, em confronto com um acelerado processo de revitalização urbana a partir dos anos 1990. Diante desse processo recente, organizações populares locais têm empreendido diversificadas lutas, como as Operações Populares de Planejamento (OPAs), cuja primeira experiência ocorreu em 2004. Busca-se conhecer em que medida essas práticas são capazes de influenciar o poder decisório que atua sobre a trama territorial local. Desse modo, o objetivo deste artigo é compreender de que modo as OPAs em Pointe-Saint-Charles se constituem em práticas de um planejamento insurgente, nos termos definidos por Miraftab (2009; 2016) e Purcell (2009). A metodologia utilizada envolveu a revisão do conceito de planejamento insurgente, além da coleta de dados primários, como depoimentos, consulta a documentos comunitários e visitas técnicas ao referido bairro montrealês. Conclui-se que as OPAs em Pointe-Saint-Charles se constituem em importantes espaços de contrapoder em relação ao planejamento urbano institucional, capazes de obter ganhos materiais e simbólicos do ponto de vista dos moradores locais. Essas práticas reúnem elementos que apontam para um campo aberto de possibilidades em relação a uma necessária mudança no planejamento urbano contemporâneo.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0130.006
Scholarly communication0.0060.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.267
Teacher spread0.238 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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