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Record W4390490288 · doi:10.34117/bjdv10n1-001

Perfil das propostas para o esporte e lazer nas candidaturas aos governos dos estados da Região Norte do Brasil nas eleições de 2022

2024· article· pt· W4390490288 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrazilian Journal of Development · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicPhysical Education and Sports Studies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Objetivou-se analisar as propostas para o esporte e/ou lazer nas candidaturas aos governos dos estados da Região Norte nas eleições de 2022. Utilizou-se pesquisa descritiva, quantitativa e documental, buscando, a partir dos descritores “esport” e “lazer”, as propostas para o esporte e lazer nas candidaturas disponibilizadas pelo site “divulgacand”. As análises foram feitas por meio de estatística descritiva. A maioria dos candidatos é do gênero masculino e os partidos políticos com mais propostas para esporte e lazer são Partido Liberal (PL) e Movimento Democrático Brasileiro (MDB). Identificou-se pequena predominância de propostas para o esporte em relação ao lazer, apesar de forte associação entre ambos. Infraestrutura prevalece para o esporte e serviços para o lazer. De modo geral, as propostas apresentam um perfil generalista, com certa ênfase na relação à educação e cultura e atendimento ao público infanto-juvenil.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.341
Teacher spread0.314 · 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