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Habilidades sociais e variáveis sociodemográficas em estudantes do ensino fundamental

2006· article· pt· W2113985384 on OpenAlexaff
Marina Bandeira, Sandra Silva Rocha, Lucas Cordeiro Freitas, Zilda Aparecida Pereira Del Prette, Almir Del Prette

Bibliographic record

VenuePsicologia em Estudo · 2006
Typearticle
Languagept
FieldSocial Sciences
TopicSocial Skills and Education
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsPsychologyHumanitiesDevelopmental psychologyPhilosophy

Abstract

fetched live from OpenAlex

As habilidades sociais são consideradas situacionais, mas há poucos estudos no Brasil relacionando-as a variáveis sociodemográficas, especialmente com crianças. Investigou-se a importância e freqüência das habilidades sociais em relação a variáveis sociodemográficas, com 257 estudantes, de 1ª a 4 ª série do ensino fundamental. Para avaliar habilidades sociais, utilizou-se o Sistema de Avaliação de Habilidades Sociais (SSRS) e, para o nível socioeconômico, o Critério Brasil. Participaram, como informantes, 185 pais e 12 professoras. Os resultados mostraram um efeito significativo do sexo, idade e indicadores socioeconômicos. Os melhores escores foram das meninas nas auto-avaliações e avaliação das professoras. A idade se correlacionou negativamente com auto-avaliação das habilidades sociais. Quanto maior a escolaridade dos pais e seu nível socioeconômico, maior o escore das habilidades sociais; quanto menor a importância atribuída pelos pais às habilidades sociais, menores os escores das crianças. O nível de habilidades sociais das crianças variou, portanto, em função de características sociodemográficas e sociais.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.321
Teacher spread0.290 · 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

Citations49
Published2006
Admission routes1
Has abstractyes

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