Navigating Food Security: How Resettlement and Social Policies Shape the Lives of Syrian Refugee Households in Canada
Bibliographic record
Abstract
This thesis investigates the impact of Canadian refugee resettlement and social policies on food security (FS) among Syrian refugees arriving after 2015. Using a convergent parallel mixed methods design, the study aims to: (1) determine the household food security (HFS) status of Syrian refugees in Saskatchewan, Ontario, and Quebec and compare it with the general Canadian population and other at-risk groups; (2) compare the HFS status across the three major Canadian refugee resettlement programs—government-assisted (GAR), privately sponsored (PSR), and blended visa office-referred (BVOR); (3) identify refugee-specific social policies affecting FS; (4) identify policy and practice gaps at federal, provincial, and local levels impacting FS; and (5) define resettlement policy barriers and opportunities for FS from the perspectives of refugees, key informants, and service providers. Data were collected through surveys of 282 Syrian refugee households and in-depth interviews with 50 Syrian refugee households and 10 key informants from federal and public service providers, NGOs, and settlement agencies. Socio-demographic and FS data were gathered using the Household Food Security Survey Module and other questionnaires used by Statistics Canada. Findings reveal high food insecurity rates among Syrian refugees, with significant variations across provinces and resettlement programs. Overall, 77% of households, 68.4% of adults, and 68.2% of children experienced some level of food insecurity (FI), with 8.2% of households facing severe FI. Quebec had a lower household food insecurity (HFI) rate (52.1%) compared to Saskatchewan (87.5%) and Ontario (79.2%), and no severe FI cases were reported in Quebec. Quebec also showed higher FS among adults, children, and households than Saskatchewan and Ontario. Severe FI was significantly higher among children living in Saskatchewan (17.6%) compared to their counterparts in Ontario (7.8%). Refugees in Saskatchewan were 3.5 times more likely to experience HFI compared to those in Quebec. Middle-income households were six times more likely to experience HFI than upper-middle-income households. GARs had a significantly higher FI rate (79.5%) compared to PSRs (62.2%), while BVORs had the highest FI rate (80.8%). There were no significant differences in the severity of FI among the resettlement programs. Factors contributing to vulnerability included resettlement location, type of program, household structure, housing tenure, education, employment status, income, and reliance on social assistance or the Canada Child Benefit. Interviews revealed that despite substantial resettlement support, several barriers at various levels affected refugees' access to food resources, traditional and preferred foods, and dietary adequacy. Key individual barriers included language skills, low income, unemployment, lack of social networks, poor mental health, and culturally based dietary perceptions. Community barriers included access to language training, social networks, and ethnic grocery stores. Institutional barriers included inconsistent support and insufficient culturally appropriate orientation programs. Social and cultural barriers involved local food culture and changes in traditional dietary practices. Policy barriers included the lack of FS-related policies, inadequate resettlement support, particularly income, and insufficient funding for service provider organizations. These findings suggest that the support systems and governmental assistance were crucial in mitigating FI but were often inadequate to address all the challenges faced by the refugees to access to food resources, traditional and preferred food, and their ability to maintain dietary adequacy and FS. The study findings offer a deeper, more comprehensive understanding of the socio-cultural, structural, and policy determinants of FS and underscore the importance of holistic and culturally sensitive approaches to addressing these challenges. The study identifies several policy and practice gaps related to refugee resettlement and FS. The study also offers important policy, practice and research recommendations. These include increasing the Resettlement Assistance Program (RAP) income amount and duration as well as revising the current income threshold policy, enhancing language support programs, improving access to affordable and appropriate housing, revising policies related to refugee resettlement location, revising the refugee sponsorship training program, establishing specialized job counselling, training, and placement programs, applying efficient coordination and information-sharing mechanisms among all players in refugee resettlement, and conducting longitudinal studies to track changes in FS status of refugees over time and through the various stages of their resettlement.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".