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Record W6999833068

Desempeño morfosintáctico en niños de 5 años provenientes de una institución educativa estatal y una institución educativa privada del distrito de Comas

2023· dissertation· es· W6999833068 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2023
Typedissertation
Languagees
FieldPsychology
TopicDevelopmental and Educational Neuropsychology
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationContext (archaeology)Christian ministryLineaWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

El estudio presentó como objetivo principal determinar si existen diferencias en el
\ndesempeño morfosintáctico entre los niños de 5 años provenientes de una institución
\neducativa estatal y una institución educativa privada del distrito de Comas. Asimismo, se
\ntrabajó con una metodología de nivel descriptiva-comparativa, con un enfoque cuantitativo,
\ndiseño no experimental y corte transversal. Estuvo integrado por una muestra de 86 alumnos
\nde ambos sexos, 41 niños pertenecientes a la institución educativa estatal y 45 de la
\ninstitución educativa privada del distrito de Comas, ello, a través de un muestreo no
\nprobabilístico. Por otro lado, para recoger datos referentes al desempeño morfosintáctico se
\naplicó como instrumento el Test exploratorio de gramática española de A. Toronto. Se
\nconcluyó que existen diferencias en el desempeño morfosintáctico estadísticamente
\nsignificativas en función al tipo de gestión educativa. La capacidad del niño para reconocer
\nestructuras gramaticales por medio de imágenes es mayor en instituciones privadas en
\ncomparación a los que estudian en estatales.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.021
GPT teacher head0.362
Teacher spread0.341 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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