Math Matters: Comparison of the Mathematics Requirements for Bachelor of Arts and Bachelor of Science Degrees in Canada
Why this work is in the frame
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Bibliographic record
Abstract
Education matters. Every year, more students are pursuing postsecondary education. In fact, during the 2012–2013 academic year, over two million students were studying in Canadian postsecondary institutions, making it even more important to ensure that our students are getting the education and training they need to succeed. Notably, it is not uncommon for university students to struggle with mathematics or even to say, “I’m bad at math.” Yet, at the heart of mathematics are critical thinking and careful questioning—skills needed in most jobs. In this paper, I feature a study exploring mathematics requirements at Canadian postsecondary institutions. Specifically, the study examines mathematics requirements for general Bachelor of Arts and Bachelor of Science degrees. The goal of the study is to offer potential suggestions to improve more students’ mathematical abilities and better prepare them for future endeavours.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it