How Governments Could Best Engage Community Organizations to Co-Design COVID-19 Pandemic Policies for Persons with Disabilities
Bibliographic record
Abstract
The COVID-19 pandemic and the policy measures adopted in response have disproportionately impacted persons with disabilities. Given the increased risk of COVID-19 and the resulting health impact for this vulnerable population, governments must engage stakeholders such as community organizations to co-design pandemic response plans. Collaboration with key stakeholders could assist in transforming services in crucial areas, such as health, where emergency policies are organized around the needs of persons with disabilities. Unfortunately, there is inadequate data collection and insufficient emergency preparedness planning and responses for persons with disabilities. This knowledge gap means consideration of health and social policy implications specific to the needs and experiences of persons with disabilities is lacking. This research study aimed to evaluate strategies through which decision-makers could engage stakeholders, such as community organizations, to co-design disability-inclusive policy responses during the COVID-19 outbreak in Alberta. Through interviews, the study focused on understanding the level of engagement, barriers to community organizations’ engagement and participatory policy aspects best suited for co-design. Key findings from the research highlighted the participants’ viewpoints on barriers, facilitators, preferences and other critical approaches through which decision-makers engage with community organizations. Results highlighted that top-down and tokenistic consultation approaches limit community organizations’ engagement in designing pandemic planning and response. Inaccessible ways of consultation and navigation barriers exacerbate obstacles to stakeholder engagement. Stakeholder engagement in data surveillance efforts was unclear, and the impact assessment process needs strengthening. The study results also showed that having COVID-19 disability advisory groups at the federal and provincial levels are a robust mechanism to connect communities with the government. However, the process of influencing government decision-making and policy actions needs to be openly communicated to civil society. Solutions are achievable. Political commitment, long-term investments and an accessible engagement environment would significantly improve stakeholder engagement. Governments must transition from traditional consultative methods to sustainable engagement practices while sharing how public policies reflect communities’ input. Financial investments must create an accessible consultation environment for designing participatory pandemic policies that reflect the priorities of persons with disabilities. Some key recommendations emerging from our analysis include: Invest financially to create an accessible consultation environment for co- designing policies. Consult stakeholders to develop new regulations or adjust existing ones to create inclusive pandemic response plans. Inform how pandemic response plans include and address community inputs and concerns in a transparent manner. Professionally contract stakeholders to co-design and communicate pandemic information. Engage with multiple stakeholders to evaluate the impact of pandemic response plans.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".