“You Are Just a Life Role Model” a Multiple Case Study of Teachers With Visual Impairment in the Field of Visual Disabilities
Bibliographic record
Abstract
Teachers with disabilities serve as role models for students who share their disability identity, offering lived experience as a valuable source of knowledge and representation. The misconceptions about the potential contributions a visual disability affords the field of education not only limit employment opportunities for individuals with visual impairment (VI) in a field with a critical shortage but also deprive students with VI of educators with a shared disability identity who could serve as role models. This qualitative multiple case study used semi-structured interviews to explore the lived experiences of seven adults with VI who pursued careers in the field of visual disabilities education. Findings indicate role modelship impacted all aspects of considering, becoming, and being a Teacher of Students with Visual Impairments (TSVI). Their professional journey was marked by a double bind; they were simultaneously perceived as unqualified due to their disability and dismissed as taking the easy route due to the shared disability identity. TSVIs with VI, however, bring critical lived experience to their teaching, advocacy, and school communities. Breaking the double bind requires collective responsibility across teacher education, policy, and school leadership. Implications for future research and practice 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".