MétaCan
Menu
Back to cohort
Record W2147975161 · doi:10.1177/002214650804900203

Capital and Context: Using Social Capital at Home and at School to Predict Child Social Adjustment

2008· article· en· W2147975161 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Health and Social Behavior · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsSocial capitalSocial mobilityContext (archaeology)Psychological interventionSocial statusIndividual capitalSocial environmentSocial reproductionStructural equation modelingSet (abstract data type)PsychologySocial psychologyEconomic capitalDemographic economicsEconomicsSociologyEconomic growthHuman capitalSocial scienceGeographyComputer science

Abstract

fetched live from OpenAlex

Research examining the influence of social relationships on child outcomes has seldom examined how individuals derive social capital from more than one context and the extent to which they may benefit from the capital derived from each. We address this deficit through a study of child behavior problems. We hypothesize that children derive social capital from both their families and their schools and that capital from each context is influential in promoting social adjustment. Using a large national data set and structural equation modeling, we find that social capital at home and at school can be measured as separate constructs and that capital at home is more influential than is capital at school. We discuss the implications of these findings for future research on social capital and for practical interventions promoting social adjustment.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.328
Teacher spread0.284 · 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