Learning from COVID-19 to enhance settlement services for refugees to Canada
Notice bibliographique
Résumé
Purpose The aim of this study is to gain knowledge about the strengths and limitations of the Canadian service delivery model in meeting the needs of the government assisted refugee (GAR) population during the COVID-19 pandemic. Design/methodology/approach This study used a qualitative case study design. Findings This aggregated case narrative identified several challenges, including an overwhelming sense of disconnection from friends and family, cultural services, access to information and access to health and social services. These complex experiences have been captured under the following themes: 1) “We do not know, yet”: Living in a Void; 2) “Limited choice”: Finding Services in a Virtual World; 3) “Between four walls”: Missing Connections; 4) “Thank you”: Staff Carrying a Burden of Compassion. Research limitations/implications This study follows a case study design that includes local responses from a small number of refugees from the Middle East. Although a small sample, this research offers detailed and rich knowledge about the settlement experience during a global pandemic in a mid-size Canadian city. This in-depth knowledge may be transferable to other contexts such as settlement of refugees in other regions across Canada. Because this study was undertaken at the beginning of the pandemic, some interviews took place online, limiting information sharing due to a lack of in-person interaction. Some settlement staff expressed reservations around sharing their experiences of providing services during the pandemic. Similarly, some newcomer families underscored their gratitude to migrate to Canada and may not have felt comfortable critiquing the system. Practical implications For settlement services going forward, having a hybrid model of services would ease the settlement experience for refugees because a combination of virtual and in-person support was noted by our participants as an effective and preferred approach. For federal and provincial governments, prioritizing internet connectivity immediately upon arrival is a key to mitigate the isolation and bewilderment that families may experience, especially amidst public health restrictions. Social implications Providing a timeline for time-sensitive information as it occurs for GARs, so GAR families and settlement workers are prompted to seek/deliver just-in-time information necessary for participants is essential to making the experience of settlement less daunting. Nation-wide implementation of the Welcome Group program is a practical step to promote a positive integration and reduce social isolation (West London Welcome, 2023). Cultural ambassadors can help with learning the language, getting to know the neighbourhood and mitigating the impact of social isolation better than if refugee families were left on their own with basic support from settlement agencies. Originality/value Recommendations for settlement service providers, and municipal, provincial and federal governments, are discussed to adapt to a mixed in-person and virtual service-delivery environment. In terms of better preparing and supporting refugees through the arrival process, there is potential to review the education and information settlement services provide for newcomers on an organizational level, including a hybrid education model, resources in more languages, attention to key timing and literacy accessibility (i.e. written, audio and video materials).
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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 | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,027 | 0,007 |
| Communication savante | 0,007 | 0,002 |
| Science ouverte | 0,003 | 0,010 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 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 ».