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Questionário de Fusão Cognitiva (CFQ): novas evidências de validade e invariância transcultural

2019· article· pt· W2944755439 on OpenAlexaff
Evandro Morais Peixoto, Giovana Corte Honda, Joël Gagnon, Tatiana de Cássia Nakano, Gláucia Mitsuko Ataka da Rocha, Daniela Sacramento Zanini, Marcos Alencar Abaíde Balbinotti

Bibliographic record

VenuePsico · 2019
Typearticle
Languagept
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

A fusão cognitiva é um conceito chave na Terapia de Aceitação e Compromisso, mecanismo em que a pessoa se funde com seus pensamentos e os toma como se fossem fatos reais. Os objetivos desta pesquisa foram de estimar novas evidências de validade do Questionário de Fusão Cognitiva (CFQ) e de testar a invariância dos itens entre amostra brasileira e franco-canadense. Participaram desta pesquisa 578 adultos brasileiros e 676 adultos franco-canadenses. A Análise Fatorial Exploratória revelou adequação da estrutura unidimensional, conforme hipótese teórica. O Rating Scale Model demostrou índices de dificuldade entre -0,42 e 0,69 e índices ajustes adequados (Infit/Outfit) entre 0,79 e 1,45 para os itens de ambas as versões e descrição sumarizada dos níveis de theta dos participantes. A Análise de DIF apontou dois itens que não suportavam invariância no parâmetro dificuldade em função das diferenças culturais. Contudo, observou-se invariância destes parâmetros quando avaliados em função do gênero dos participantes de cada amostra.

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)0.035
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.112
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
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 head0.032
GPT teacher head0.393
Teacher spread0.361 · 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 designBench or experimental
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

Citations2
Published2019
Admission routes1
Has abstractyes

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