Exploring strategies on how the Government of Alberta could best engage community organizations to co-design pandemic-related policies and interventions for persons with disabilities.
Notice bibliographique
Résumé
Persons with disabilities and their families are disproportionately impacted by the COVID-19 pandemic and the policy measures adopted in response. Given the increased risk for this vulnerable population group, the governments must engage stakeholders like community organizations and families of persons with disabilities to plan and co-design pandemic response plans. Harnessing experiential knowledge of and fostering collaboration with such stakeholders could aim in transforming services in crucial areas like health, where emergency policies and programs are organized around the needs of persons with disabilities. Initiatives that enhance civil society participation in designing policies and programs create a more transparent and responsive government and improve government programs' buy-in. Unfortunately, there is inadequate data collection and insufficient emergency preparedness planning and response for people with disabilities. The goal of this research was to identify the critical barriers from the government perspective while exploring best engagement strategies for co-designing rapid policy responses during the COVID-19 outbreak in Alberta. Twelve qualitative interviews with key decision-makers from provincial, municipal governments and disability advisory groups’ members were conducted. Using semi-structured interviews, the participants were asked open-ended questions on key thematic areas to address the research objective. Key findings from the research highlighted the participants’ viewpoints on barriers, aspects and preferences, which are the critical approaches through which the Government of Alberta engages with community organizations. First, health emergency policy responses need to view disability and poverty as interconnected factors to improve the overall quality of life for persons with disabilities. Findings also highlighted that top-down and tokenistic consultation approaches further limit the disability community's engagement in co-designing pandemic planning and response. Furthermore, inaccessible ways of consultation and navigation barriers exacerbate the impediments to a holistic co-design process. Findings also revealed that communication of pandemic information in accessible formats and tools is the most preferred co-design aspect to engage community organizations in developing a pandemic response. On the other hand, stakeholders' engagement in the government’s data surveillance efforts was unclear, and the overarching process of impact assessment needs to be strengthened. The research found that the COVID-19 disability group and the advisory council's presence at the federal and provincial levels is a robust mechanism that connects communities with the government. However, the process of influencing government decision making and policy actions needs to be openly communicated. The research recommends that governments transition from traditional consultative approaches to innovative engagement practices while sharing information on how public policies reflect communities’ input. Decision-makers are further recommended to make financial investments to include priorities of persons with disabilities in the pandemic planning and response. The decision-makers should also formally engage stakeholders like community organizations to co-design communication aspects of the pandemic response plan, along with the monitoring and evaluation of the plan. Medical or cultural barriers pose challenges for persons with disabilities to participate in co-designing policies. Further research is required to explore how families of persons with disabilities could be engaged to co-design public policies and interventions.
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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 | 0,012 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,018 | 0,010 |
| Communication savante | 0,011 | 0,004 |
| Science ouverte | 0,003 | 0,011 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 ».