Research and Education in Accessibility, Design, and Innovation (READi) : A Reflection of Our First Year
Bibliographic record
Abstract
Research and Education in Accessibility, Design, and Innovation (READi) is an interdisciplinary training program focusing on accessibility. With the first year of the READi completed, this paper provides an overview of the design of the program and reflections from the program, as experienced by two of its trainees. The training program appears to have increased the knowledge and skills of student trainees with regard to accessibility, while also enhancing many professional skills. In addition, there appears to be affective learning, uplifting the thoughts, opinions, and feelings of accessibility and inclusion, that foster a culture of accessibility. The program benefits from interdisciplinarity, collaborations with external stakeholders, engagement with real-world accessibility issues, and inclusion of people with disabilities.
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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 | 0.031 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.024 |
| Insufficient payload (model declined to judge) | 0.002 | 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".