Bibliographic record
Abstract
• According to handicapped students, what are the factors that make their studies easier or harder? • What are the differences and the similarities between students with handicaps and those without? • What can cégeps do to improve the quality of life and graduation rates for handicapped students? 16 PÉDAGOGIE COLLÉGIALE VOL. 19 NO 4 ÉTÉ 2006 In North America, between 5 and 11 % of students at postsecondary level in North America have one or more handicaps. These are the fi ndings of a Pan-Canadian study carried out by our team. The research shows that almost all Canadian postsecondary institutions have handicapped students enrolled; that only one-third to one-half of students with disabilities are registered for services available for the handicapped at their college or university; and lastly, that there is a higher percentage of handicapped students enrolled in Canadian colleges (including cégeps) than in universities (3.74% versus 1.62 % 1). Québec has approximately ten times fewer students with disabilities enrolled at postsecondary level than all other provinces: 0.5 % versus 5.5 % for the remainder of the country (Fichten et al., 2003). These studies were recently reproduced for
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".