Achievement on the Ontario Secondary School Literacy Test: a focus on immigrant students
Bibliographic record
Abstract
This study explored the achievement of students from a large Ontario school board on the 2004-2005 Ontario Secondary School Literacy Test, using multilevel modeling. There was a focus on the achievement gap between Canadian-raised and immigrant students. Significant student-level predictors were years since immigration, home language, home neighbourhood income, age, gender, absenteeism and program of study. Significant school-level predictors were school percentage in the academic program, school percentage immigrant, whether the school reported absenteeism and school size. Program of study was a strong predictor, even stronger at the school than at the student level. There were significant cross-level interactions between school percentages academic and immigrant and the variables measuring years since arrival in Canada, indicating that the achievement of immigrant students was affected by school context. The majority of the variance was at the student level although significant variance of the school intercepts remained in the full model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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; both teacher heads agree on what is shown here.
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".