How Governments Could Best Engage Community Organizations to Co-Design COVID-19 Pandemic Policies for Persons with Disabilities
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,014 | 0,008 |
| Communication savante | 0,015 | 0,009 |
| Science ouverte | 0,003 | 0,016 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».