Advancing disability equity in academic workplaces: a professional development seminar case study
Bibliographic record
Abstract
Although about a quarter of working age adults in the United States identify as disabled, representative numbers are not found in most workplaces, including academic and scientific workplaces. In higher education, disability-focused policies, programming, professional development, as well as research, have been predominantly oriented toward disabled learners. This by-default attention to the needs of disabled students implicitly signals that disabled faculty and staff are not expected to be present, and/or are not welcomed and valued employees. In this evaluative case study, we detailed a year-long professional development seminar investigating experiences of academic faculty who identify as disabled and reviewed findings from a post-seminar survey. Taken together, the quantitative and qualitative survey data indicated that participants in the seminar series made meaningful gains in four fundamental aspects of allyship focused on disability (in)equities in academic workplaces: increased general topical knowledge of disability stereotyping and discrimination, improved understanding of discriminatory impacts of ableism, enhanced skills for interrupting disability discrimination and inequities, and amplified personal commitment and motivation for addressing disability equity in the workplace.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".