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Qual é o perfil motivacional característico de tenistas infanto-juvenis brasileiros?

2012· article· pt· W2001586228 on OpenAlexaff
Marcos Alencar Abaíde Balbinotti, Luciano Juchem, Marcus Levi Lopes Barbosa, Ricardo Pedrozo Saldanha, Carlos Adelar Abaide Balbinotti

Bibliographic record

VenueMotriz Revista de Educação Física · 2012
Typearticle
Languagept
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Motivação, na Teoria da Autodeterminação (TAD), é entendida como a chave principal do bom funcionamento psicológico do indivíduo e de seu bem-estar geral. De acordo com esta teoria, o "Prazer" é a dimensão que melhor explica o comportamento humano autodeterminado. Este estudo descreve o perfil motivacional característico de tenistas infanto-juvenis brasileiros e explora possíveis diferenças significativas nas médias das dimensões que integram o perfil avaliado pelo Inventário de Motivação à Prática Regular de Atividades Físicas e/ou Esportivas (IMPRAFE-126), controladas pela variável "Sexo". Uma amostra de 226 tenistas gaúchos e catarinenses, com idades entre 13 e 16 anos. Os resultados indicam que a dimensão que mais motiva esses tenistas, independente do sexo, é o Prazer, seguida, respectivamente, pelas dimensões: Competitividade, Saúde, Sociabilidade, Estética e Controle de Estresse. Além de este resultado ser um importante indicador à formulação de modelos de treino, uma das principais conclusões é que este estudo confirma a teoria de base.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.037
GPT teacher head0.335
Teacher spread0.298 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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