Workshop report: Intersecting identities—gender and intersectionality in physics
Bibliographic record
Abstract
The concept of intersectionality refers to how our various social identities (e.g., gender, race, class) overlap to create power, privilege, or marginalization. We report on a workshop held at the International Conference for Women in Physics, where physicists discussed equity in physics through an intersectional lens. The workshop content was informed by data from around the world and research from the social sciences. The workshop had a total of three sessions, was designed to be highly participatory, and included interactive group activities and extensive discussions. From the discussions that took place, several recommendations emerged for IUPAP, for the IUPAP Working Group 5 (WG5) and for the country team leaders of the ICWIP conferences. Recommendations included addressing intersectionality in IUPAP policies and initiatives, and encouraging further collaboration with social scientists.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".