DIMENSIONES DE LA PERSONALIDAD Y TIPOS DE ALEXITIMIA EN ADOLESCENTES
Bibliographic record
Abstract
La presente investigación busca la relación entre las dimensiones de la personalidad\nsegún Eysenck y presencia de alexitimia en adolescentes de Instituciones Educativas\nPrivadas y Públicas de UGEL – SUR Arequipa; con la finalidad de comprobar si existe\nla presencia de alexitimia en adolescentes con dimensión de la personalidad\nintrovertida. Nuestra investigación es de tipo correlacional y de corte transversal.\nPara la evaluación de dicha relación entre alexitimia y personalidad extrovertida e\nintrovertida se usó dos pruebas: el Inventario de Personalidad EPQ - Forma A (Hans J.\nEysenck - Sybul B.G Eysenck) y la Escala de Alexitimia de Toronto TAS 20 (Bagby,\nTaylor y Parker, 1985. Adaptación de Martínez – Sánchez (1996)); a modo de\ncomprobar la comprensión se aplicó una prueba piloto a 17 adolescentes.\nAdicionalmente para el análisis de datos se empleó la hoja de cálculo de Excel 2013 con\nsu complemento analítico y el paquete SPSS v.22.0.\nDe esta manera se pudo concluir que existe una relación inversa significativa entre la\npersonalidad y la alexitimia en adolescentes de UGEL – SUR Arequipa; la personalidad\nintrovertida se relaciona con una alta alexitimia, predomina en varones y mujeres la\npersonalidad extrovertida, y las mujeres tienden a tener mayor alexitimia que los\nvarones.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".