Bibliographic record
Abstract
This chapter uses a retrospective lens to highlight cultural factors affecting lesbian, gay, bisexual, transgender, queer, and allied (LGBTQA+) communities, focusing on a community-based intervention that advances LGBTQA+ people in the STEM (Science, Technology, Engineering, and Mathematics) disciplines. Within these fields, there is a dearth of both metrics and resources supporting people with sexual and gender minority identities. Over the last two decades, the 501(c)(3) non-profit, oSTEM (Out in STEM) Incorporated, was created to help address these lapses, and it continues to broadly advance LGBTQA+ people in STEM. The oSTEM leadership cultivated a community of skilled and diverse people, building bridges across identities while celebrating differences, and the community includes both students and professionals from the United States, Canada, United Kingdom, and beyond. In 2012, oSTEM collaborated to produce the first quantitative study on Factors Impacting the Academic Climate for LGBQ STEM Faculty (Patridge et al. 2014). To date, oSTEM has coordinated more than ten annual conferences, reaching hundreds of chapters and thousands of people. The collective efforts of oSTEM align with the sentiment of “unity through diversity.”
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".