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Neighborhood and Family Influences on Educational Attainment: Results from the Ontario Child Health Study Follow-Up 2001

2007· article· en· W2143917982 on OpenAlexaffabout
Michael H. Boyle, Katholiki Georgiades, Yvonne Racine, Cameron Mustard

Bibliographic record

VenueChild Development · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsEducational attainmentPsychologyDisadvantagedMultilevel modelDevelopmental psychologyDemographyFamily incomeAcademic achievementExplained variationLongitudinal studyStatisticsSociology

Abstract

fetched live from OpenAlex

This study uses multilevel models to examine longitudinal associations between contextual influences (neighborhood and family) assessed in 1983 in a cohort of 2,355 children, 4-16 years of age, and educational attainment in 2001. Variation in educational attainment in 2001 attributable to between-neighborhood and between-family differences was 8.17% and 36.88%, respectively. The final model explained 33.64% of the variance in educational attainment, with unique variances of 14.53% for neighborhood and family-level variables combined versus 10.94% for child-level variables. Among the neighborhood and family-level variables, indicators of status (5.29%) versus parental capacity/family process (4.03%) made comparable predictions to attainment while children from economically disadvantaged families did not benefit educationally from living in more affluent areas.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.085
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.040
GPT teacher head0.308
Teacher spread0.268 · 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

Citations113
Published2007
Admission routes2
Has abstractyes

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