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Evaluación de la empatía diádica: Análisis de las propiedades psicométricas del Índice de Reactividad Interpersonal en Parejas (IRIC-C) en contexto chileno

2014· article· es· W2141787969 on OpenAlexaff
Mónica Guzmán González, Katherine Péloquin, Marie‐France Lafontaine, Caterina Trabucco, Alfonso Urzúa

Bibliographic record

VenuePsicoperspectivas Individuo y Sociedad · 2014
Typearticle
Languagees
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsCanadiana.orgUniversity of OttawaUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

En los últimos años, la empatía se ha incorporado como una variable que permite comprender diversos aspectos del funcionamiento en las relaciones de pareja, lo cual hace necesario contar con instrumentos validados que permitan evaluar este constructo. El presente estudio tuvo como objetivo evaluar las propiedades psicométricas de la versión chilena del Indice de Reactividad Interpersonal para Parejas (IRIC-C) en dos muestras independientes: una de estudiantes universitarios (N = 612) y otra de población general (N = 766) de la ciudad de Antofagasta, Chile. Los índices de consistencia interna fueron adecuados para la escala de toma de perspectiva, sin embargo, no alcanzaron los niveles óptimos para la preocupación empática. El análisis factorial confirmatorio corroboró la estructura bidimensional del instrumento y la invarianza métrica entre hombres y mujeres. Asimismo, se presenta evidencia acerca de la validez discriminante del instrumento. Los resultados son discutidos en términos de sus implicancias, aportes y limitaciones.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.022
GPT teacher head0.366
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2014
Admission routes1
Has abstractyes

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