Making the Unknown or Invisible Accessible: The Collaborative Development of Inclusion-Focused Open-Access Case Studies for Principals and Other School Leaders
Bibliographic record
Abstract
Gaps between research and practice exist in the field of inclusive and special education, especially around school-based leadership (e.g., principals). Research-based case studies are a way to teach and learn about disability, especially stigmatized issues such invisible disability (e.g,. intellectual disability), which may be complex with multiple stakeholders, yet difficult to access. This article reviews the collaborative process of developing and disseminating authentic case studies built on lived experiences of school principals as an example of bridging the gap between research and practice with multiple, engaging knowledge mobilization activities. Future knowledge mobilization activities, such as the development of interactive, online case-based based learning around inclusive classrooms and schools, are discussed.
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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 | 0.262 | 0.286 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.009 | 0.043 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".