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Record W1967792447 · doi:10.3200/joer.98.2.109-114

Effects of Neighborhood Socioeconomic Characteristics and Class Composition on Highly Competent Children

2004· article· en· W1967792447 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Journal of Educational Research · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocioeconomic statusDemographyContrast (vision)Social classDevelopmental psychologyPsychologyGeographySociologyPolitical sciencePopulationPhysics

Abstract

fetched live from OpenAlex

The conditions that prevent highly competent children from fully developing their learning potential rarely have been addressed. The authors investigated the relationship between neighborhood socioeconomic characteristics, class composition, and changes in the proportion of highly competent children in kindergarten and in Grades 4 and 7. The authors used cross-sectional data from 78 Vancouver, British Columbia, schools to conduct a series of multipleregression analyses. Results show that the proportion of highly competent kindergarten children was correlated weakly with neighborhood socioeconomic status. In contrast, in Grades 4 and 7, the proportion of highly competent kindergarten children was correlated strongly with neighborhood socioeconomic factors. In addition, the proportion of children at risk was strongly and increasingly correlated with the proportion of highly competent children in kindergarten and in Grades 4 and 7.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.026
GPT teacher head0.356
Teacher spread0.330 · 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