Effects of Neighborhood Socioeconomic Characteristics and Class Composition on Highly Competent Children
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it