The Effects of School Quality and Family Functioning on Youth Math Scores: a Canadian Longitudinal Analysis
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Bibliographic record
Abstract
This paper tries to disentangle the relative importance of family and school inputs on a child's cognitive achievement as measured by her percentile score on a mathematics test. We replicate a study by Todd and Wolpin (2007) in the United States with Canadian data. In contrast to their work that uses state-level indicators of school quality, we estimate our model with data from Statistics Canada's National Longitudinal Survey of Children and Youth (NLSCY) which provides micro-level information on the family and school history of the child. The sample used for the analysis is based on the 7- to 15-year old longitudinal children who have completed at least two consecutive math tests. As in Todd and Wolpin, we conclude that cognitive outcomes are determined by current and past family inputs. Contrary to them, who find no impact of school inputs, we find that the quality of schools has a positive impact on achievement in mathematics.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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