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Record W2022290552 · doi:10.1037//0022-006x.70.2.378

Do places matter? Socioeconomic disadvantage and behavioral problems of children in Canada.

2002· article· en· W2022290552 on OpenAlexaffabout
Micheal H. Boyle, Ellen L. Lipman

Bibliographic record

VenueJournal of Consulting and Clinical Psychology · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsHamilton Health SciencesMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsSocioeconomic statusDisadvantagedPsychologyDisadvantageDemographyDevelopmental psychologyPopulationSociology

Abstract

fetched live from OpenAlex

This study evaluated the influence of neighborhoods and socioeconomic disadvantage on behavioral problems rated by parents and teachers in a nationally representative sample of children ages 4 to 11 years living in Canada. Between-neighborhood variation accounted for 7.6% and 6.6% of parent and teacher ratings, respectively. About 25.0% of this neighborhood variation could be explained by socioeconomic variables evenly divided between neighborhood and family-level measures. Family socioeconomic status, lone-parent family status, and percentage of lone parents in neighborhoods were strong, reliable predictors of behavioral problems. Ratings were contextualized: Fewer behavioral problems were assessed in children from well-off families living in disadvantaged neighborhoods, whereas more problems were assessed in children from poor families living in advantaged neighborhoods.

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)0.002
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 score0.022
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
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 head0.111
GPT teacher head0.497
Teacher spread0.386 · 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

Citations98
Published2002
Admission routes2
Has abstractyes

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