Canadian Physics Counts: An exploration of the diverse identities of physics students and professionals in Canada
Bibliographic record
Abstract
The lack of diversity in physics remains a persistent worldwide problem. Despite being a quantitative discipline which relies on measurements to construct and validate hypotheses, there remains a paucity of data on both demographics and experiences of marginalized groups. In Canada, there has never been a nationwide assessment of those studying or working in physics. Here, we present findings from Canadian Physics Counts: the first national survey of equity, diversity, and inclusion (EDI) in the Canadian physics community. Our intersectional approach allowed us to gather a wealth of information on gender identity, sexual orientation, race, disability, and more. Analyses revealed key findings, including the first data on physicists who identify as non-binary or gender diverse, as well as the first data on Black and Indigenous scholars. Black physicists (1.2%) and Indigenous physicists (.3%) were found to be the most underrepresented, while White men were overrepresented across all sectors. Among respondents with a disability, 5% reported receiving full accommodations for their required needs at their place of work or study. One in four respondents from BIPOC gender diverse backgrounds identified as being disabled, and the proportion of sexually diverse students who reported having a disability was more than three times higher than the proportion of heterosexual students with a disability. The data also revealed that students represented more demographic diversity than working professionals, highlighting the importance of acting today in order to retain the diverse physicists of tomorrow. Our analysis identifies areas for intervention and offers recommendations for building a diverse and inclusive physics community in Canada that can be a global exemplar.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".