'It's just my home, you know?' Home-making and Belonging for People Labelled/with Intellectual Disability
Bibliographic record
Abstract
This master’s thesis research focuses on the experiences of people labelled/with intellectual disability in their current homes and also what they want for their future home. Few studies in Canada have focused on specifically asking this population what their ideal home looks like and acknowledging the gap between this and what their reality is. Advocacy groups in Canada and the United Nations Convention on the Rights for Persons with Disabilities have been calling for years to better address the rights of people with disabilities and their place in the community, yet there has been little progress within Ontario towards this. Using semi-structured interviews and an arts workshop, participants were asked to think about what their life is like now and what their aspirations are for their future. The research is based on a relational model of home as more than just a physical structure and expands the definition to include the neighbourhood, relationships, and support that participants experience, which shape their home and their feelings of belonging inside and outside of it. Findings show that, while there were opportunities for agency within their homes and relationships, there are many restrictions to attaining their ideal home, including funding constraints, long wait lists, and few choices for what type of housing they receive. The findings of this study have important implications for ideas of belonging and processes of home-making within geographic research, as well as for future policy based on housing for people labelled/with intellectual disabilities in Ontario.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".