Improving Social Policy with National Data: A Comparison of Social Support for Students Among Canadian Provinces
Bibliographic record
Abstract
Abstract: The purpose of this study was to examine social support for students as it related to individual and provincial characteristics in Canada, with data from the National Longitudinal Survey of Children and Youth and census data. The data included 7,648 students aged 8 to 11 years from 10 provinces. Factor analysis indicated two latent factors underlining social support for students: perceived personal support and perceived institutional support. Results of hierarchical linear modelling show that perceived personal support did not fluctuate with provincial characteristics. Students who were immigrants to Canada, with low socioeconomic status (SES), and with poor prosocial behavior perceived less personal support. Students in provinces with higher birth rates perceived less institutional support. SES and family size had strong effects on perceived institutional support in some provinces but weak effects in other provinces. Students from both-parent households, with emotional problems, and from large families perceived less institutional support.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".