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Record W4385562815 · doi:10.4025/jphyseduc.v34i1.3415

Itinerários de combate da Federação Paraense de Luta Marajoara

2023· article· pt· W4385562815 on OpenAlexaff
Carlos Afonso Ferreira dos Santos, Welison Alan Gonçalves Andrade, Rogério Gonçalves de Freitas

Bibliographic record

VenueJournal of Physical Education · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicPhysical Education and Sports Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste artigo foi analisar os primeiros passos da recém-criada Federação Paraense de Luta Marajoara (FPLM), e compreender quais os possíveis impactos de sua governança na escolarização e esportivização desta luta. Nesta pesquisa, de cunho qualitativo, a técnica utilizada para a reunião dos dados foi a entrevista não diretiva. Os participantes da pesquisa foram dois membros da FPLM. Constatou-se que a FPLM como instituição autoreguladora estrutura suas propostas de escolarização e esportivização em um contexto de governança esportiva centralizada, estabelecendo-se como detentora de um monopólio sobre a Luta Marajoara ao idealizar intenções voltadas ao impulsionamento local e regional dessa luta brasileira. Contudo, a pesquisa conclui que o longo caminho de “combate” da FPLM se dará entre sua concepção prática autoreguladora em contraste ao sentido crítico e democrático para o reconhecimento da Luta Marajoara.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.050
GPT teacher head0.417
Teacher spread0.367 · 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 designObservational
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

Citations4
Published2023
Admission routes1
Has abstractyes

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