Clima social familiar y alexitimia en jóvenes universitarios de ciencias sociales
Bibliographic record
Abstract
En la presente investigación se buscó encontrar la posible relación entre las dimensiones del \nClima Social Familiar y el nivel de Alexitimia en jóvenes estudiantes del sexto y octavo \nsemestre de las escuelas profesionales de la Facultad de Ciencias Tecnológicas Sociales y \nHumanidades de la Universidad Católica de Santa María; con la finalidad de saber si existe una \ninfluencia del Clima Social Familiar en el incremento de los niveles de Alexitimia en la muestra \nanteriormente mencionada. Esta investigación es de tipo descriptivo correlacional. Los \ninstrumentos empleados fueron: La Escala del Clima Social en Familia FES (R.H. Moos y E.J. \nTrickett) y la Escala de Alexitimia Toronto TAS–20 (M. Bagby, J. Parker & G. Taylor; 1994. \nAdaptación Kendall y Rodríguez; 2003). \nSe llegó a la conclusión que no existe una relación significativa entre el Clima Social \nFamiliar como variable general, sin embargo, se encontró que la dimensión de relaciones \nperteneciente al Clima Social Familiar y la Baja Alexitimia tienen una correlación negativa \nentre sí. Así mismo, se llegó a la conclusión que, de acuerdo al género, la mayoría de mujeres \ntienen niveles bajos de alexitimia, mientras que los hombres tienen niveles más altos de \nalexitimia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".