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Record W3123092061 · doi:10.33081/formacao.v27i52.7418

PRIVAÇÃO SOCIAL COMO CONCEITO DE ANÁLISE DA POBREZA URBANA: APONTAMENTOS TEÓRICOS

2021· article· pt· W3123092061 on OpenAlexfundno aff
Pedro Leonardo Cezar Spode, Rivaldo Mauro de Faria

Bibliographic record

VenueFormação (Online) · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicUrban Development and Societal Issues
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSociologyHumanitiesGender studiesPhilosophy

Abstract

fetched live from OpenAlex

Ao longo das décadas, a Geografia vem se utilizando de uma gama de conceitos para entender a pobreza e as desigualdades socioespaciais e territoriais, sobretudo nas cidades. Entretanto, muito pouco se dialogou, especialmente na Geografia Urbana, a respeito da privação social, conceito nascido na Sociologia, e utilizado em diversos campos da ciência, como Psicologia Social, Economia, Saúde Pública, entre outros. Dessa maneira, visando contribuir no aprofundamento do conceito, este texto busca estabelecer um ensaio teórico a respeito da noção de privação social, buscando uma abordagem histórica do conceito, desde sua formação na Sociologia, na metade do século XX, às definições mais recentes, dentro de diferentes enfoques teóricos e metodológicos. Nesse sentido, são definidos três períodos de desenvolvimento teórico da privação social, o primeiro se iniciando na década de 1940, com Sociólogos como Samuel Stouffer e Robert K. Merton, o segundo a partir da década de 1960, com autores como Peter Towsend e Walter G. Runciman. O terceiro momento sendo caracterizado pela difusão do conceito para análise das desigualdades em diversas disciplinas, como na Economia, na Geografia e na Saúde Pública.

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)0.006
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: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0050.013
Scholarly communication0.0100.008
Open science0.0010.003
Research integrity0.0010.002
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 head0.084
GPT teacher head0.350
Teacher spread0.265 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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