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Validez de contenido del Cuestionario de Ciberagresión

2021· article· es· W3194368910 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Evaluar · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicEducational Outcomes and Influences
Canadian institutionsTrinity College
Fundersnot available
KeywordsHumanitiesPhysicsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

El propósito de este trabajo es presentar el proceso de validación de contenido del Cuestionario de Ciberagresión diseñado en Irlanda por Corcoran y Mc Guckin (2014). En este estudio instrumental participaron 15 jueces locales, con experticia y trayectoria en la temática, quienes ponderaron cuantitativa y cualitativamente el cuestionario. Se han tomado en cuenta todas las aportaciones realizadas en el análisis cualitativo. Los datos cuantitativos se sistematizaron utilizando el coeficiente V de Aiken complementado con el uso de intervalos de confianza. Los resultados indican un amplio grado de acuerdo entre los jueces, en la medida en que presentan intervalos de confianza superiores a .50. Por todo ello, se concluye que el Cuestionario de Ciberagresión es una herramienta adecuada para medir dicho constructo en adolescentes escolarizados de Argentina. El presente estudio ofrece el primer instrumento en español válido para medir dicho fenómeno.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.041
GPT teacher head0.403
Teacher spread0.362 · 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