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Record W2942063521 · doi:10.3895/cgt.v6n21/22.6121

A polarização dos corpos desejantes

2011· article· pt· W2942063521 on OpenAlexaff
Guaraci da Silva Lopes Martins

Bibliographic record

VenueCadernos de Gênero e Tecnologia · 2011
Typearticle
Languagept
FieldSocial Sciences
TopicGender, Sexuality, and Education
Canadian institutionsQuest University Canada
FundersUniversidade Tecnológica Federal do Paraná
KeywordsPhilosophyHumanitiesSociology

Abstract

fetched live from OpenAlex

O presente artigo resulta do interesse na investigação sobre as relações de poder associadas à subjetividade dos corpos. Para tanto, desenvolveu-se uma análise com base no filme Meninos não Choram sob a direção de Kimberly Pierce, obra artística que contribui para o processo de questionamento de discursos que tendem à manutenção de hierarquias socialmente construídas e manifestadas em diferentes formas de opressão contra o feminino. Ainda que seja alvo de discriminação, de exclusão, de evasão escolar, esta temática permanece à margem das discussões no ambiente escolar. Considera-se que ao contrariar normas e regras que transitam pela via dos discursos, tal como Brandon/Tenna, protagonista do referido filme, muitos estudantes também desestabilizam limites de fronteira entre o masculino/ feminino. Assim, o filme analisado é um estímulo à reflexão sobre as identificações consideradas arbitrárias acerca da heteronormatividade e sobre a urgente necessidade de estratégias políticas e pedagógicas comprometidas com novas abordagens sobre os processos socioculturais envolvidos na construção das identidades.

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)0.003
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 score0.028
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.007
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.002

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 head0.255
GPT teacher head0.360
Teacher spread0.105 · 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
Published2011
Admission routes1
Has abstractyes

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