University Inclusion Practices – Re-Encountering the Status Quo: An Interpretive Approach
Bibliographic record
Abstract
Abstract My aim is to forge a feel for the importance of building critical understandings of common forms of engagement with disability and in this way work against the careless-care that seems to surround the ways disability-experience is managed in education. First, I discuss what this interpretive dse approach entails. Second, I narrate being in the University classroom with my dyslexic ways and counterpose this to “access statements” on course outlines which are now a common occurrence in the Canadian context. I then conduct an interpretive analysis of the meaning of disability as it appears through my personal story and these bureaucratic statements of inclusion. Despite these differing instances of inclusion, I show how both maintain the status quo of university work-life. Through a politics of wonder, this paper aims to invigorate life affirming relations where disability might figure as something other than a pharmakon for the status quo.
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.022 | 0.109 |
| Scholarly communication | 0.026 | 0.022 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.009 |
| 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".