Vamos falar sobre ciência: aproximação da ciência na prática do profissional de educação física na residência multiprofissional
Bibliographic record
Abstract
OBJETIVO: Contextualizar o uso das ferramentas metodológicas e relatar as experiências com a disciplina de “Avaliação e Prescrição de Atividade Física para a Saúde e Doença” ministrada para profissionais/residentes de Educação Física (EF). MÉTODOS: O artigo apresenta as descrições de atividades desenvolvidas para dois profissionais da primeira turma de residência multiprofissional da Universidade Estadual do Centro-Oeste (Unicentro-PR). Buscou-se inovar em aspectos do ensino, utilizando como referência metodológica a atividade física baseada em evidências e aprendizagem baseada em problemas.RESULTADOS: Entre as experiências destacadas estão a importância da busca por referencial teórico e os momentos de aplicação dos conteúdos na prática, e a contextualização dos ensaios pragmáticos fomentando reflexões sobre a prática no âmbito da atenção primária à saúde (APS).CONCLUSÃO: Espera-se que esse relato propicie a discussão continuada nos cursos de residência multiprofissional sobre a otimização da aplicação da ciência na prática dos profissionais de EF no contexto da APS.ABSTRACT. Let’s talk about science: approximating science and practice of exercise professionals in the multidisciplinary residence.OBJECTIVE: To contextualize the use of methodological tools and report the experiences with the course “Assessment and Prescription of Physical Activity for Health and Disease” ministered for professionals/residents in Physical Education (PE). METHODS: The article presents the descriptions of activities developed for two professionals of the first class from the multidisciplinary residence of the Midwestern Parana State University (Unicentro-PR). We aimed to innovate in teaching aspects, using methodological references such as evidence-based physical activity and program-based learning. RESULTS: There are some highlighted experiences such as the importance of searching for the theoretical reference and the timing to apply the topics, optimizing the application of science in the residences’ practice and the pragmatic trials stimulating evidences that reflects practices.CONCLUSION: We hope this report provides the continuous discussion on multidisciplinary residence courses about the optimization of science applied into practice by PE professionals in the primary health care context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".