Criar con inteligencia emocional: sentir, validar y acompañar desde el respeto
Bibliographic record
Abstract
Este episodio está dedicado a la inteligencia emocional en la infancia. Se explica el concepto, su historia y su importancia en el desarrollo de habilidades sociales, como la empatía, la regulación emocional y la capacidad de resolver conflictos. La psicóloga Carolina Labrador destaca que esta inteligencia se construye desde la crianza y las interacciones con los cuidadores, quienes deben brindar atención y disciplina positiva. El programa desmonta mitos sobre la disciplina positiva, aclarando que no significa permisividad, sino establecer límites desde el respeto y la comprensión. Se ofrece orientación sobre cómo validar las emociones de los niños sin reprimirlas, utilizando frases y gestos adecuados, y cómo vincular esas emociones con actividades de aprendizaje o actos de reparación. Se enfatiza que las emociones no se controlan, sino que se atienden y escuchan. El ejemplo adulto, la gestión emocional de los padres y el acompañamiento afectivo son claves para el desarrollo de esta inteligencia. Finalmente, se brindan recomendaciones para padres sobre cómo manejar sus propias emociones para criar desde la calma y la conciencia.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".