Looking in the mirror: Attitudes toward disability
Bibliographic record
Abstract
This paper serves as a foundational piece, aiming to investigate the potential of critical disability theory (CDT) and disability critical race theory (DisCrit) in shedding light on students' perceptions of their own exceptionalities and how this can impact their educational achievement in subjects like math, physical education, and English. While there is a substantial body of research focusing on CDT, teacher attitudes, and non-identified student attitudes towards disabilities, there is a lack of research exploring the connections between CDT, DisCrit, and students' attitudes towards their own exceptionalities. It is crucial to acknowledge how students perceive their own exceptionalities, as internalizing ableist prejudice and discrimination can lead to students viewing their exceptionalities as hindrances or barriers, which can detrimentally affect their academic development. However, by embracing the activist work of CDT and DisCrit scholars and shifting ableist perspectives towards a strengths-based approach that highlights individuals' resilience and fortitude. This shift in mindset has the potential to enhance students' overall academic success.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".