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Record W2161499340 · doi:10.1080/15374410701444363

Testing the 8-Syndrome Structure of the Child Behavior Checklist in 30 Societies

2007· article· en· W2161499340 on OpenAlexaff
Masha Y. Ivanova, Thomas M. Achenbach, Levent Dumenci, Leslie Rescorla, Fredrik Almqvist, Sheila Weintraub, Niels Bilenberg, Héctor Bird, Wei J. Chen, Anca Dobrean, Manfred Döpfner, Neşe Erol, Éric Fombonne, António Castro Fonseca, Alessandra Frigerio, Hans Grietens, Helga Hannesdóttir, Yasuko Kanbayashi, Mike Lambert, Bo Larsson, Patrick W. L. Leung, Xianchen Liu, Asghar Minaei, Mesfin S. Mulatu, Torunn Stene Nøvik, Kyung Ja Oh, Alexandra Roussos, Michael Sawyer, Zeynep Şimşek, Hans‐Christoph Steinhausen, Christa Winkler Metzke, Tomasz Wolańczyk, Hao‐Jan Yang, Nelly Zilber, Rita Žukauskienė, Frank C. Verhulst

Bibliographic record

VenueJournal of Clinical Child & Adolescent Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsCBCLChild Behavior ChecklistChecklistMulticulturalismPsychologyMental healthConfirmatory factor analysisClinical psychologyDevelopmental psychologyStructural equation modelingPsychiatry

Abstract

fetched live from OpenAlex

There is a growing need for multicultural collaboration in child mental health services, training, and research. To facilitate such collaboration, this study tested the 8-syndrome structure of the Child Behavior Checklist (CBCL) in 30 societies. Parents' CBCL ratings of 58,051 6- to 18-year-olds were subjected to confirmatory factor analyses, which were conducted separately for each society. Societies represented Asia; Africa; Australia; the Caribbean; Eastern, Western, Southern, and Northern Europe; the Middle East; and North America. Fit indices strongly supported the correlated 8-syndrome structure in each of 30 societies. The results support use of the syndromes in diverse societies.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.389
Teacher spread0.328 · 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 teacher head, not a consensus.

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

Citations421
Published2007
Admission routes1
Has abstractyes

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