Validación del “Toronto Empathy Questionnaire (TEQ)” en una Muestra Uruguaya
Bibliographic record
Abstract
ResumenLa evaluación de la empatía se ha realizado a través de diferentes escalas de autorreporte que estudian aspectos afectivos o cognitivos del constructo.A pesar de la aceptación actual de las escalas multidimensionales, se ha sugerido que es posible evaluar una dimensión general subyacente, siendo el Toronto Empathy Questionnaire (TEQ) una técnica desarrollada para este propósito.Este estudio analizó las propiedades psicométricas del TEQ en una muestra de 200 adultos uruguayos (100 mujeres, 100 hombres).El análisis factorial mostró un buen ajuste para el modelo unidimensional.Eliminando 10 ítems se alcanza la unidimensionalidad esencial.Los resultados sugieren que la versión del TEQ en español es válida para la población en estudio.Se sugiere revisar la formulación de los ítems invertidos y la validez de la versión reducida de 6 ítems.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".