A statistical analysis of finding the best predictor of success in first year calculus at the University of British Columbia
Why this work is in the frame
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Bibliographic record
Abstract
In this thesis we focus on high school students who graduated from a B.C. high school in 1985 and then proceeded directly to the University of British Columbia (UBC) and registering in a first year calculus course in the 1985 fall term. From this data, we want to determine the best predictor of success (the high school assigned grade for Algebra 12, or the provincial grade for Algebra 12, or the average of the high school and the provincial grade for Algebra 12) in first year calculus at UBC. We first analyze the data using simple descriptive statistics and continuous methods such as regression and analysis of variance techniques. In subsequent chapters, the categorical approach is taken and we use scaling techniques as well as loglinear models. Finally, we summarize our analysis and give conclusions in the final chapter.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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