MétaCan
Menu
Back to cohort
Record W1669215213

VARIABLES MODERADORAS DE LA CONVIVENCIA ESCOLAR EN EDUCACIÓN PRIMARIA

2012· article· es· W1669215213 on OpenAlexaboutno aff
Iván Antonio, Lucía Herrera Torres

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PsychologyTUTORPerceptionPrimary educationPedagogyDevelopmental psychologyGeography
DOInot available

Abstract

fetched live from OpenAlex

El objetivo del presente trabajo es analizar la percepción que el alumnado de Educación Primaria tiene acerca de la convivencia escolar en función de distintas variables de comparación: sexo, edad y entorno sociocultural. Para ello, participaron 546 alumnos del primer curso de cada ciclo de Educación Primaria procedentes de dos centros educativos de la Ciudad Autónoma de Melilla con características sociales y culturales diferentes. Como instrumento de recogida de datos se empleó una versión adaptada del Cuestionario sobre Convivencia Escolar para Alumnos de Sánchez, Mesa, Seijo, Alemany, Rojas, Ortiz, Herrera, Gallardo y Fernández (2009). El cuestionario fue administrado por los tutores y contestado por los alumnos en el tercer trimestre del curso escolar 2009-2010. Tomados en su conjunto, los resultados obtenidos muestran una convivencia escolar adecuada, aunque no exenta de ciertos conflictos. Además, se ponen de manifiesto diferencias en relación con las distintas variables de comparación. Finalmente, se discute la necesidad de desarrollar programas preventivos con el fin de controlar aquellas actitudes y conductas que pudieran estar influyendo negativamente en la convivencia escolar.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.172
GPT teacher head0.585
Teacher spread0.414 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicSocial Sciences and PoliciesFrench-language works237,207