Higher education for students with intellectual disability: expanding research, policy, and practice
Bibliographic record
Abstract
This chapter describes the emerging higher education options for students with intellectual disability (ID) in the United States and other countries. Access to higher education has become more available to students with ID in recent years, impacting the knowledge and practices used in secondary and higher education. In the United States, much of the program development activity has been connected to federal legislation and funding. In other countries such as Australia, Canada, Ireland, and Portugal, these initiatives are less driven by national agendas or funding but are implemented in a more localized manner by specific universities or communities. Background information on the development of these initiatives and the focal issues for program development, research, and policy for the past decade will be provided across these diverse contexts. The chapter concludes by highlighting next generation issues, such as faculty training and personnel preparation, credential development, and program accreditation.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".