When a Seat at the Table is not Enough: A Participatory Action Research Study on Collaborative Partnerships in Ontario Developmental Services Organizations
Bibliographic record
Abstract
Historically, Ontario’s developmental services (DS) has evolved largely guided by the knowledge and direction of non-disabled service providers and government. However, the UN Convention on the Rights of Persons with Disabilities promotes the participation of people labeled with disabilities in decision-making processes about the programs and policies that impact their lives. Existing theories and literature reveal the importance of collaborative partnerships where power is shared with service users through participatory decision-making, shared leadership, and opportunities to participate with influence. Four self-advocates labeled with developmental disabilities collaborated as co-researchers in this participatory action research study to explore what model of collaborative partnerships best met the inclusion goals of service users labeled with developmental disabilities in these settings. Nine adult service users labeled with developmental disabilities and twelve leaders/managers of eight Ontario DS organizations participated in virtual semi-structured interviews. Thirteen service users participated in two focus groups. Findings suggest a model of collaborative partnerships that may meet service users’ goals for inclusion is a strategy of participation that positions service users as experts and partners with the power to effect change and integrates their expertise at each level of the organization and each stage of the service delivery cycle. This model is composed of key elements, which fall within three supportive layers: a supportive organizational culture, inclusive and influential methods of participation, and supported and committed members. What becomes clear through these key elements is the need for a human rights and democratic approach to participation whereby service users are positioned as expert citizens and right bearers welcomed into the design and provision of services that affect their lives. Such a shift is best facilitated through systems change and a shift in power at multiple levels.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".