Social Network and Support Experiences of Older African Refugees in Calgary: A Visual Story
Bibliographic record
Abstract
The intersection of ageing and forced migration carries profound health and psychosocial implications for older immigrants. These implications are particularly acute for older refugees, who, having been compelled to flee their home countries, often encounter compounded vulnerabilities such as poverty, language barriers, cultural dislocation, and age-based discrimination. As a result, older refugees represent one of the most marginalised and underserved subgroups within the broader refugee population. Despite these significant challenges, their experiences remain comparatively underexamined in both academic literature and humanitarian discourse, especially when juxtaposed with the attention afforded to other vulnerable groups such as women and children. This invisibility exacerbates the risk of older refugees falling through systemic and intervention gaps. In many developing contexts, particularly in African countries, older adults often rely on informal networks, such as family, kinship systems, and community structures, for support during times of crisis. However, the forced displacement associated with migration often severs these traditional sources of care and solidarity, thereby heightening the precarity and isolation experienced by older African refugees in host countries. This study adopts a qualitative, arts-informed approach—specifically visual diagramming and storytelling—to explore the social network experiences of older African refugees residing in Calgary. Following ethics approval from the University of Calgary Conjoint Faculties Research Ethics Board (CFREB), data were collected from 11 participants (10 women and one man) in three phases. The first phase elicited participants’ migration narratives through the use of personal timelines and storytelling. The second phase examined their current social networks and support systems using ecomaps, complemented by narrative accounts. In the third and final phase, preliminary findings were presented to participants for validation, feedback, and further elaboration. All data were transcribed and imported into NVivo 14©, a Computer-Assisted Qualitative Data Analysis Software (CAQDAS), where they were coded and organised into thematic nodes. Textual data were analysed using narrative analysis, while visual data (timelines and ecomaps) were interpreted through case-based analysis. Findings reveal that many older African refugees experienced a profound loss of social capital and communal support as a result of their traumatic migration journeys, which were frequently precipitated by armed conflict or political violence. Nonetheless, the principle of Ubuntu—a philosophy rooted in collective care and shared humanity—emerged in several narratives, with some participants receiving informal support from residents in their host communities. The older refugees continued to report persistent challenges post-migration, in Calgary, including language barriers, limited educational or vocational qualifications, deteriorating physical and mental health, and systemic racism. The loss of traditional support networks further compounded their social isolation. Participants also voiced disappointment with the culturally grounded support systems that they had hoped to rely on, such as ethnic associations and faith-based organisations, which they felt had not met their specific cultural and emotional needs. Despite these adversities, older African refugees continue to make significant contributions to Calgary's economic and cultural life through paid and volunteer labour, intergenerational knowledge transfer, and community leadership. The findings of this thesis underscore the urgent need for intentional and inclusive approaches to the settlement and integration of older African refugees. Key recommendations include addressing language and technological access barriers, developing culturally responsive programming, and recognising the social, cultural, and economic contributions of older refugees. By centring their lived experiences and amplifying their narratives, this study contributes to a more equitable and culturally attuned understanding of the refugee experience—one that not only highlights the structural and interpersonal challenges they face but also affirms their resilience, agency, and enduring contributions in contexts of resettlement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".