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Record W3157559348 · doi:10.4025/jphyseduc.v31i1.3150

O que são life skills e como integrá-las no esporte brasileiro para promover o desenvolvimento positivo de jovens?

2020· article· pt· W3157559348 on OpenAlexafffund
Vitor Ciampolini, Michel Milistetd, Sara Kramers, Juarez Vieira do Nascimento

Bibliographic record

VenueJournal of Physical Education · 2020
Typearticle
Languagept
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of Ottawa
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorGovernment of Canada
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

O esporte tem sido apontado como uma ferramenta valiosa para promover o desenvolvimento positivo de jovens (DPJ). Além disso, o desenvolvimento de life skills destaca-se por auxiliar jovens a ter sucesso dentro e fora do contexto esportivo. Devido as discussões limitadas no Brasil acerca do DPJ e das life skills tanto no âmbito científico quanto na estruturação de programas esportivos, este ensaio teórico tem como objetivo fornecer entendimentos iniciais a acadêmicos, treinadores e gestores esportivos sobre as concepções que sustentam estas temáticas e como integrá-las no esporte brasileiro. Assim, após explorar as concepções e definições acerca do DPJ e das life skills e as abordagens para o desenvolvimento no esporte, os autores apresentam uma proposta baseada em três princípios e cinco procedimentos. Os princípios incluem: (a) reflita e desenvolva sua filosofia; (b) cultive um clima positivo e (c) desenvolva relações significativas com seus atletas. Já os procedimentos são: (1) selecione e discuta a life skill do dia; (2) pratique a life skill selecionada; (3) integre a life skill com as atividades do treino; (4) discuta e reflita a aplicação e transferência da life skill para outros contextos e (5) crie oportunidades para facilitar a transferência da life skill. Exemplos práticos são fornecidos ao longo da proposta para auxiliar treinadores na aplicação ao esporte.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.346
Teacher spread0.319 · 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; both teacher heads agree on what is shown here.

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

Citations17
Published2020
Admission routes2
Has abstractyes

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