Against Exclusion: Intellectual and Developmental Disability Policy in Canada
Bibliographic record
Abstract
Within Canada, the social inclusion of people with intellectual and developmental disabilities (IDD) is impeded by structural and social barriers borne from a legacy of systemic discrimination and policies of explicit exclusion. This exclusion is so ingrained that the realization of ‘full inclusion’ for this population significantly challenges dominant social and political norms. However, despite this challenge, for the past 25 years social inclusion has been at the forefront of the Canadian disability policy agenda. This dissertation poses two related research questions: (1) ‘how is social inclusion framed in the design and implementation of policies targeting people with IDD?’, and (2) ‘how do Canadian provinces differ in the effectiveness of social services that promote the social inclusion of people with IDD?’ \nThese questions are addressed in three phases. The first phase involves a Critical Frame Analysis of IDD policy designs within relevant federal and provincial policy documents, identifying six distinct design frames. In the second phase, IDD policy implementation processes are assessed for how they (re)frame social inclusion. Empirical support is drawn from interviews and focus groups with policy actors, advocates, and service users. While the complex nature of implementation (re)framing in IDD services confounds cross-provincial comparison, this dissertation introduces a novel typology for comparing implementation decisions. It demonstrates that policy effectiveness need not be confined to mechanisms of top-down accountability and can be achieved through empowering implementers to adhere to professional norms or service user preferences. \nThis empirical analysis of social inclusion policy (re)framing develops a descriptive foundation to select and weight indicators used in the third phase: a multidimensional policy index. The Social Inclusion Services Index (SISI) comprises 10 indicators across 4 domains that capture the effectiveness of Canadian IDD policies in promoting social inclusion. The SISI offers insight into the finding that, despite widespread support for inclusive IDD policy, implementation has failed because of austere spending, stalled policy transitions and inflexible administrative structures, among other factors. Cross-provincial comparison, based on indicators reflecting priorities identified by study participants, highlights areas of emphasis to curtail policy failure in the promotion of social inclusion for Canadians with IDD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".