SOCIALLY DISADVANTAGED SUDENTS IN SOCIALLY DISADVANTAGED SCHOOLS: DOUBLE JEOPARDY IN MATHEMATICS ACHIEVEMENT IN THE G8 COUNTRIES
Why this work is in the frame
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Bibliographic record
Abstract
Using the G8 countries’ (Canada, France, Germany, Italy, Japan, the Russian Federation, the United Kingdom, and the United States) samples from the 2003 Programme for International Student Assessment (PISA), this study aimed to explore the phenomenon of double jeopardy in mathematics achievement for socially disadvantaged students. Double jeopardy is a situation of dual penalties where coming from low socioeconomic status (SES) families and attending low SES schools results in concurrent penalties at both the student level and school level in mathematics achievement. This study examined the phenomenon of double jeopardy in the G8 countries across four school locations: rural regions, towns, cities, and metropolitan areas. This study also examined four separate definitions of socioeconomic status in order to determine the effectiveness of each definition. The four definitions corresponded to four SES measures utilized in this study: father’s SES, mother’s SES, family occupation SES, and combined family SES. Multilevel analysis with students nested within schools indicated that significant double jeopardy effects varied according to SES measure, school location, and country. However, the majority of the double jeopardy effects across all the variables were large in magnitude. Furthermore, the combined family SES and the metropolitan school location were often the most sensitive SES measure and school location, respectively, to double jeopardy in the G8 countries.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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