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Early childcare and physical aggression: differentiating social selection and social causation

2004· article· en· W2119022260 on OpenAlexafffundabout
Anne I.H. Borge, Michael Rutter, Sylvana M. Côté, Richard E. Tremblay

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2004
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité de Montréal
FundersUniversitetet i OsloSocial Sciences and Humanities Research Council of CanadaMolson Foundation
KeywordsAggressionPsychologyDevelopmental psychologyCausationPoison controlSocial environmentInjury preventionDay careSuicide preventionClinical psychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Some research findings have suggested that group day-care may be associated with an increased risk for physical aggression. METHODS: Cross-sectional maternal questionnaire data from a representative sample of 3431 Canadian 2- to 3-year-olds were used to compare rates of physical aggression shown by children looked after by their own mothers and those attending group day-care. A family risk index (using occupational level, maternal education, size of sibship, and family functioning) was created to test whether any difference in physical aggression might reflect social selection rather than social causation. RESULTS: Aggression was significantly more common in children looked after by their own mothers than in those attending group day-care. Strong social selection associated with family risk was found, not only in the sample as a whole, but even within the high-risk subsample. However, after taking social selection into account, physical aggression was significantly more common in children from high-risk families looked after by their own parents. No such difference was evident in the majority (84%) of children from low-risk families. CONCLUSION: Insofar as there are any risks for physical aggression associated with homecare they apply only to high-risk families.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.409
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.310
Teacher spread0.298 · 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.

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

Citations97
Published2004
Admission routes3
Has abstractyes

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