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Record W7001087487

Influencia de la disfunción familiar en el rendimiento académico en estudiantes de enfermería de la Universidad Alas Peruanas

2019· dissertation· es· W7001087487 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2019
Typedissertation
Languagees
FieldSocial Sciences
TopicSocial Skills and Education
Canadian institutionsnot available
Fundersnot available
KeywordsOddsTest (biology)Quarter (Canadian coin)Sample (material)
DOInot available

Abstract

fetched live from OpenAlex

La presente investigación tiene como objetivo determinar si la disfunción familiar influye en el rendimiento académico en estudiantes de la Universidad Alas Peruanas. Siendo un estudio de tipo analítico, observacional, retrospectivo de casos y controles. La población de estudio estuvo constituida por 46 estudiantes según criterios de inclusión y exclusión establecidos distribuidos en dos grupos: con rendimiento académico inadecuado o adecuado, se calculó el odds ratio y la prueba chi cuadrado. Los resultados indican que no se apreciaron diferencias significativas para las variables edad, sexo ni procedencia entre los estudiantes de uno u otro grupo de estudio. La frecuencia de disfunción familiar en estudiantes con rendimiento académico inadecuado fue 47 %. La frecuencia de disfunción familiar en estudiantes de enfermería con rendimiento académico adecuado fue 17 %. La disfunción familiar es factor asociado a rendimiento académico inadecuado en estudiantes de enfermería con un odds ratio de 4.35 el cual fue significativo (p<0.05). Se concluye que la disfunción familiar influye en el rendimiento académico en estudiantes.

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)0.006
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.359
Teacher spread0.353 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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