Self-reported assistive technology outcomes and personal characteristics in college students with less-apparent disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The impact of assistive technology (AT) services for college students with less-apparent disabilities is under-reported. Using the Canadian Occupational Performance Measure (COPM), we assessed student Performance and Satisfaction ratings of common academic tasks at the start and end of a semester during which 105 student-clients with less-apparent disabilities received AT services. We examined if COPM scores related to personal characteristics of gender, class-level (e.g., Sophomore), and STEM education; if personal characteristics predicted a student's follow-through with an AT service referral (n=231); and if personal characteristics and initial COPM scores predicted dropout from AT services (n=187). COPM ratings significantly increased in all academic tasks (p<.001). Gender predicted initial Satisfaction (male ratings > female ratings; p=.01), and Performance changes (females were more likely to have a service-meaningful change; p=.02). Higher class-level predicted better follow-through with a referral for AT services (p=.006). Increasing class-level (p=.05) and higher initial studying (p<.006) and reading (p<.029) ratings predicted a lower likelihood for dropout. These findings demonstrate that college students with less-apparent disabilities experience substantial improvements in their self-ratings of academic performance and satisfaction following AT services. Gender, class-level, and initial self-perceived reading and studying abilities may influence if and how the student participates with AT services.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 it