Bibliographic record
Abstract
This dissertation interrogates the disconnection between rights-based, accessibility-related policy and the actual experience of disability in the context of Toronto. This work is informed by my own experience of moving through the world with a disability. Five Torontonians with disabilities were interviewed about their experiences finding housing, work, and accessing transportation within the GTA. These experiences were contrasted with how disability is articulated as an issue of rights by referring to the Access for Ontarians with Disabilities Act (AODA) as an example of accessibility-related legislation. My work is animated by the philosophy of a “politic of difference,” as theorized by Jeff Noonan and relies on the theoretical framing of Dorothy E. Smith’s writing. Working with these influences, I draw on the concept of “standpoint theory” and “ruling relations” to triangulate lived experience and policy with the reality of inclusion. Moving beyond traditional sociology, I bring together a mosaic of information that connects my experience and the experience of interview subjects with policy as well as the reality of inclusion and access within the city. Accessibility and disability-related legislation is erroneously written as if access and inclusion is a destination rather than an interaction informed by the community and its inherent social and physical barriers. The notion that the destination of accessibility has been reached creates a disconnect between the lived experience of people with disabilities and legislation. This thesis asserts that inclusion and accessibility need to be re-animated as relational concepts rather than a destination, moving past a culture of minimal compliance to a politic of difference, and reveals that access and inclusion is very much made the burden of the individual who is disabled. Instead of people authentically engaging with the relational nature of access and its many nuances, this dissertation details how the current situation in Ontario follows a minimal legal standard of access, implementing a superficial approach to inclusion that is normalized today.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.051 | 0.046 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".