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Record W2057314641 · doi:10.1192/bjp.179.2.110

Family settings and children's adjustment: differential adjustment within and across families

2001· article· en· W2057314641 on OpenAlexaff
Thomas G. O’Connor, Judy Dunn, Jennifer M. Jenkins, K.T. Pickering, Jon Rasbash

Bibliographic record

VenueThe British Journal of Psychiatry · 2001
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of Toronto
FundersMedical Research Council
KeywordsStepfamilyPsychosocialPsychologyDevelopmental psychologySiblingPsychopathologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Children in stepfamilies and single-parent families exhibit elevated levels of behavioural and emotional problems compared with children in intact (biological) families, but there is variation within and across these family types. AIMS: To examine the sources of variation in children's behavioural and emotional problems across diverse family settings. METHOD: Levels of behavioural and emotional problems in children from diverse stepfamilies and single-parent families were compared with children living with both biological parents. Psychosocial risks were measured at the individual child and family levels. RESULTS: Behavioural and emotional problems were elevated in children in stepmother/complex stepfamilies and single-parent families, but not in simple stepfather families, relative to 'biological' families. Psychopathology associated with family type was explained by compromised quality of the parent-child relationship, parental depression and socio-economic adversity. Sibling similarity in behavioural and emotional problems was most pronounced in high-risk family settings. CONCLUSIONS: Family type is a proxy for exposure to psychosocial risks; the extent of family-wide influence on children's development may be strongest in high-stress settings.

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)0.000
metaresearch head score (Gemma)0.003
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
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.266
Teacher spread0.255 · 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

Citations117
Published2001
Admission routes1
Has abstractyes

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