Proposta de conteúdos tático-técnicos para o desenvolvimento de atletas de basquetebol de 15 à 19 anos
Bibliographic record
Abstract
The process of developing athletes is a long-term and non-linear process, which is influenced by several factors, including tactical-technical content.Coaches play different roles and functions that are fundamental in the long-term development process of athletes, such as the organization, selection, application and evaluation of tactical-technical content.The objective of this dissertation was to identify the tactical-technical contents for the elaboration of proposals for the development of young basketball athletes in Brazil, from international documents and from the perspective of coaches with experience in under-15 to under-19 men's basketball teams in Brazil.To this end, we identified the tactical-technical content for the development of athletes from the under-15 to under-19 categories described in the documents of the countries best placed in the FIBA ranking: Argentina, Australia, Canada, Spain and the United States.To analyze the perspective, knowledge and experiences of coaches of the Brazilian men's basketball teams from under-15 to under-19, semi-structured interviews were carried out, later analyzed through thematic analysis.The results were organized based on attack, transition and defense contents, which are the technical-tactical aspects and tactical-technical aspects.The coaches highlighted the importance of the long-term development of basketball athletes, based on a progression of contents, which develops the technical-tactical aspects in the initial categories, in order to enhance the development of present and future tactical-technical aspects.They also highlighted the importance of understanding the concept of advantage and disadvantage, both offensive and defensive, in addition to pointing out the lack of international experience of Brazilian athletes from the under-15 to under-19 categories as a detrimental factor in the sports development and better results of these teams in international competitions.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".