SOCIAL CAPITAL AND DISPARITIES IN CANADIAN YOUTH’S MATHEMATICS ACHIEVEMENT
Bibliographic record
Abstract
This article examines the influence of youth’s family and school contexts in order to understand disparities in Canadian youth’s mathematics achievement. Using hierar‐ chical linear analysis, some of the main assumptions of social capital theory are tested using the Canadian data from the 1999 Programme for International Student Assess‐ ment. Findings revealed that many family‐school contextualized effects were not sig‐ nificant, suggesting that researchers need to look at the conceptualization and opera‐ tionalization of social capital. Relationships between family structure and some measures of school social and were, however, found to be significant. Results suggest that the similarity hypothesis needs to be further analyzed and perhaps integrated into social capital theory. Key words: family, school, PISA, booster effect, double jeopardy effect, mitigating effect Dans cet article, l’auteure analyse les influences des contextes familiaux et scolaires dans lesquels les jeunes évoluent en vue de comprendre comment ces contextes créent des disparités dans les résultats qu’ils obtiennent en mathématiques. Utilisant des données canadiennes tirées du Programme international pour le suivi des acquis des élèves (PISA) de 1999, l’auteure a testé ses hypothèses à l’aide d’une analyse linéaire hiérarchique. Ses résultats révèlent qu’un grand nombre des effets contextualisés familiaux et scolaires n’étaient pas statistiquement significatifs, ce qui donne à penser que les chercheurs doivent se pencher sur la conceptualisation et l’opérationalisation du capital social. Certaines relations entre la structure familiale et diverses mesures du capital social et humain dans les écoles se sont toutefois avérées significatives. Les résultats semblent indiquer que l’hypothèse de similarité a besoin d’être analysée davantage et peut‐être intégrée dans la théorie du capital social. Mots clés : famille, école, PISA, effet stimulant, effet double obstacle, effet atténuant
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".