Gender Issues in Mathematics: An Ontario Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In many developed countries, including Canada, it is often perceived that gender issues in mathematics have been ‘solved’ and are no longer a relevant and timely issue. In this article, I challenge this perception by providing an overview of gender issues in mathematics in three domains – achievement, attitude, and participation – ranging from the elementary school level to the university level. My analysis of several sources of data from Ontario is compared to a meta-analysis of research involving data from culturally similar countries to Canada (e.g., Australia, United Kingdom). The data primarily arise from large-scale mathematics assessments (e.g., PISA, EQAO) and national statistics databases (e.g., Statistics Canada, National Center for Education Statistics). Counter to the aforementioned perception, this analysis indicates that gender issues still exist in mathematics in developed countries, including Canada. The gender gap is particularly wide in terms of students’ attitudes and participation: Males have substantially more positive attitudes toward mathematics and higher levels of participation in non-mandatory levels of mathematics than do females. The article concludes with a discussion of the implications of the findings and suggestions of possible steps that may be taken to help ameliorate the current situation.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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