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Record W2801175064 · doi:10.5628/rpcd.16.02.77

O desenvolvimento do taekwondo como esporte paralímpico

2016· article· pt· W2801175064 on OpenAlexaboutno aff
Jacqueline Martins Patatas, Édison Duarte, José Júlio Gavião de Almeida

Bibliographic record

VenueRevista Portuguesa de Ciências do Desporto · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Para-taekwondo is the adaptation of the Olympic sport enabling the practice of people with physical and motor disabilities.In 2015, parataekwondo joined the Paralympic Movement and will make its debut at Tokyo 2020 Paralympic Games.Due to this recent trajectory, it is still not possible to find in the literature many scientific studies concerning para-taekwondo.Therefore, the aim of this study is to analyze the parataekwondo coaches' perspective regarding the evolution of the sport, since its genesis until the inclusion in the paralympic program.Seven taekwondo coaches, all male, with taekwondo graduation above 4th DAN, coming from Canada, Brazil, Mexico, Guatemala and Venezuela participated in this study.All coaches who participated in the study were part of the national teams of their countries and had more than ten years of experience within the sport.Through a semi-structured interview, questions were raised in order to understand the development of parataekwondo in the American Continent.The data were analyzed using the content analysis method proposed by Bardin (2002).It was possible to conclude that the new parasport is still in a stage of constant development, even after establishing itself as a paralympic sport.Concerning this matter, it is essential that actions aiming the improvement of the professional training for all the coaches and professionals who are involved in the area are implemented, resulting in a better work towards people with disabilities.

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)0.006
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.045
GPT teacher head0.350
Teacher spread0.305 · 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 designNot applicable
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

Citations1
Published2016
Admission routes1
Has abstractyes

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