Enacting Power at the Decision-Making Table: Foregrounding the Voices of People with Intellectual and Developmental Disabilities in the Policy Process through Engagement with Families in Relational Self-Advocacy
Bibliographic record
Abstract
Self-advocacy by people with intellectual and/or developmental disabilities (IDD) has long been an important driver of collective empowerment and social recognition for the IDD movement. In recent years, new avenues to mobilization (including the increased involvement of self-advocates within formal advocacy groups and the growth of self-advocacy networks through social media and online communities) have led to more direct engagement by self-advocates in processes of policy consultation at the governmental level. Still, despite advancements in inclusion practices, there remain significant questions as to whose voices are foregrounded (i.e., are the most prominent), and to what extent policymakers meaningfully engage with self-advocates. By contrast, family advocates have historically had more opportunities than self-advocates to engage directly with political institutions. Family advocates have been instrumental both in advocacy group formation and pursuit of the legal enshrinement of IDD rights, paving the way for significant policy advances. The present paper assesses the commonalities and cleavages between self-advocacy and family advocacy, with specific attention to the historical evolution of IDD advocacy in Canada. The comparison is framed by addressing two primary objectives of IDD advocacy: i) promoting authentic individual and collective counter-narratives (i.e. the lived experiences of people with IDD that challenge dominant ableist assumptions) and ii) effecting policy change. We conclude by examining the interconnectivity of the two forms of advocacy and the potential of relational approaches based on interdependence and social connection of people with IDD and their close supports to overcome pervasive social and political institutional barriers.
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.048 | 0.058 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".