EXPERIENCES OF TRANSITION FROM UNIVERSITY TO KNOWLEDGE WORK FOR GRADUATES WITH LEARNING DISABILITIES
Bibliographic record
Abstract
There is a growing number of students with disabilities accessing postsecondary education in Ontario. Among this student body, students with learning disabilities are the largest sub-group. These students transition into knowledge workplaces, which have significant cognitive performance standards. Although there is some emerging literature on the outcome of university graduates with learning disabilities, there is little known about their experiences during this transition process. There are two central purposes of this doctoral thesis: a) to provide insight into the experiences of transition for university graduates with learning disabilities, and b) to critically reflect upon the practicalities and politics of implementing participatory action research. The papers gathered in this dissertation are based upon a participatory action research project with mentees, and interviews with both mentees and mentors from a learning disability mentorship program at an Ontario university. The first paper is a collaborative writing piece with co-researchers that applies an analogy of ‘taking center stage’ to reflect upon the process of participation for co-researchers. The second paper involves a critical reflection of the imagined distance that took place amongst the research team, and an exploration of participatory techniques to address this distance. The third paper examines qualitative interviews with mentors and mentees on three stages of the transition process: interview, general cognitive ability testing and probationary period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".