Cultivating Disability Leadership: Implementing a Methodology of Access to Transform Community-based Learning
Bibliographic record
Abstract
In this paper, we describe a methodology of access developed and applied during a three-year project in the Niagara region focused on cultivating the next generation of disability leaders. We describe the theoretical approach to the project and highlight the significance of doing this work in Niagara. A literature review of adult, transformative, and community-based learning scholarship revealed that little research or writing has focused on describing a thorough approach to access in transformative projects in community-based settings. Writing with two participants from the study, we elaborate on the five dimensions of our approach: 1) funding; 2) local and focused; 3) intimate, relational, and interdependent; 4) curating access, and 5) welcoming disruption. We also describe the tensions in taking on this work. We conclude with an invitation to scholars, community groups, and organizations to consider integrating our methodology in their next research project.
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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 | 0.034 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| 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".