Striving for Equity in Canadian Physics
Bibliographic record
Abstract
We discuss a number of new initiatives and events since 2020 which we hope will contribute to advancement of equity issues within the physics community in Canada. A recent analysis of high-school data shows that men are still over-represented in high-school physics courses, and the fraction has not changed in over a decade. Results from a national survey show that despite improvements over the years, the percentage of women and gender diverse physicists drops by around 35% between undergraduate students to those in a physics career. This decline is even more notable among Black, Indigenous, and people of colour (BIPOC) women and gender diverse physicists, whose representation drops by almost 60%. Several programs from the National Sciences and Engineering Research Council (NSERC) have been implemented in order to improve equity, diversity, and accessibility in STEM on a national level, most notably the Chairs for Women in Sciences and Engineering (CSWE) and Chairs for Inclusion in Sciences and Engineering (CISE) initiatives. It is crucial to maintain data collection and support existing as well as new EDI projects in future years as we work to build a more inclusive community of physicists in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.045 | 0.008 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".