Postsecondary Education and Disability, 15(1), 28-58. Comparison of Student And Service Provider Perspectives
Bibliographic record
Abstract
In a series of three studies conducted between fall 1997 and spring 1999 we explored the computer, information and adaptive computer technologies needs and concerns of Canadian postsecondary students. To obtain an overview of the important issues, in Study 1 we conducted focus groups with 6 postsecondary personnel responsible for providing services to students with disabilities and 12 postsecondary students with various disabilities. In Study 2 we obtained in-depth information from Canada-wide structured interviews with individuals responsible for providing services to students with disabilities (n=30) and with 37 postsecondary students with various disabilities. In Study 3 we collected comprehensive information via questionnaire from a Canada-wide sample of 725 junior/community college and university students as well as data about the proportion of students with disabilities from 162 campus based disability service providers. Here we report on the scientific aspects, including the methods used and the findings. In a companion article (Fichten, Asuncion, Barile, Fossey, Robillard, & Wolforth, 2001) we use the findings to generate wide-ranging recommendations and provide resources and tools for practitioners.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".