Intersections between and understandings of literacy and disability in a B.Ed program: Discourses, tensions and curriculum
Bibliographic record
Abstract
This study contributes to the growing body of research that seeks to destabilize dominant notions of literacy and disability. In particular, we explore teacher candidates’ understandings and constructions of literacy and children with “special needs”, or children identified as having a “learning disability”, before and after they complete their kindergarten-grade six teacher certification (B.Ed). We examine how dominant discourses of dis/ability present themselves in these teacher candidates’ initial and subsequent understandings, and how courses and a tutoring practicum can and cannot work to open up new ideas about literacy and dis/ability. Our intention is to add to the discussions of literacy education and curriculum informed by sociocultural and critical disability theory. This study highlights the connections between literacy and dis/ability as they intersect and are inextricably intertwined throughout the discourses and tensions seen in the data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".