Enseñanza de la Técnica Ne-Waza en el Rendimiento Académico de Estudiantes con Discapacidad Auditiva de Educación General Básica
Bibliographic record
Abstract
The present study was applied in the Juan Pablo II Fiscomisional Specialized Educational Unit, located in the City of Esmeraldas in 8 students with hearing disabilities from the fourth to seventh year of basic education during the second quarter, with the application of activities of the technique of Ne-Waza of Judo, considered a Japanese martial art, the practice of this technique involves holding movements towards the ground, the purpose is to improve interpersonal relationships through leadership, teamwork and responsibility, constant practice strengthens the patterns of respect for the opponent, continuous repetition and discipline, the purpose of the study was to improve academic performance in the study subjects. A research was applied with a quantitative and qualitative approach, of a pre-experimental type, where it was possible to verify academic performance in basic subjects such as: Mathematics, Language, Natural Sciences and Social Sciences, after the application of the SPSS v.25 statistician, determined that the average academic record of the first quarter was 8.18 ± 0.20 points and after the application of the intervention, at the end of the second quarter the average was 8.58 ± 0.20 points, in conclusion it was demonstrates that the application of the Ne-Waza technique exercises improve the academic performance of students with hearing disabilities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".