Transnational Activities and their Impact on Achieving a Successful Housing Career in Canada: The Case of Ghanaian Immigrants in Toronto
Bibliographic record
Abstract
Appropriate housing with security of tenure is an important factor in the immigrant settlement and integration process. However, many studies of immigrant settlement and the housing careers of immigrants do so within the borders of a nation-state without reference to transnationalism – immigrants’ ties and cross-border connections with the country of origin. This case study of the transnational ties and housing careers of Ghanaian immigrants in Toronto aims to increase our understanding of one recent immigrant group’s settlement and integration process in Canada. Using a mixed-method approach involving both quantitative and qualitative data collection methods, this study explores how transnational housing activities influence the housing careers of Ghanaians in Toronto. The findings include insights into the immigration history and the socio-demographic characteristics of Ghanaians in Toronto; the nature and extent of transnational ties between Ghana and Canada; the nature of housing careers among Ghanaians in Toronto; and the influence of transnationalism on housing careers of Ghanaians in Toronto. \nAlthough Ghanaians’ immigration to Canada dates from the late 1950s, Ghanaians started coming to Canada in noticeable numbers after the 1960s. Ghanaian immigration to Canada generally and to Toronto particularly surged in the 1980s and beyond. Deteriorating economic and political conditions in Ghana and relatively favourable immigration policies and a good economic climate in Canada were the driving forces behind Ghanaian migration to Canada. However, the Ghanaian settlement process in Toronto does not culminate in a complete break with the homeland. Rather, Ghanaians in Toronto have engaged in a range of transnational activities with the country of origin, including contacts with family and friends, travelling to or visiting Ghana, following Ghanaian politics, investing in housing or property in Ghana, running businesses in Ghana, attending funerals in Ghana, and making regular remittances to Ghana. \nWith respect to Ghanaians’ housing careers, the study reveals that during their initial settlement period, most Ghanaians lived in public subsidized rental housing or poor-quality private rental housing. They considered their housing conditions as inadequate and unsuitable and were not satisfied with their neighbourhood’s safety and security. At the time of the survey, however, respondents were more likely to own homes and were more likely to feel safe and secure in their neighbourhoods. However, housing affordability remains a major problem for Ghanaians in Toronto. With respect to the influence of transnationalism on housing careers of Ghanaians in Toronto, the study finds that transnational housing activities, especially Ghanaians’ attitudes to and preference for investing in housing in Ghana, affect their housing careers in Toronto. Sending regular remittances to Ghana and investing in housing in the homeland involve mobilizing huge financial resources from Toronto to achieving their housing needs in the country of origin, while many Ghanaians struggle to meet their own needs in Toronto. A logistic regression analysis shows that personal income and strong ties with Ghana are statistically significant predictors of investing in housing in Ghana. At the same time, significant predictors of Ghanaians’ propensity to own a house in Canada include loyalty to Canada and household income.\nThe study contributes conceptually and empirically to three areas of research – transnationalism, housing careers, and immigrant settlement and integration – which hitherto have been studied as separate themes. Conceptually, it breaks away from the traditional way of researching immigrant settlement and housing careers by introducing a new conceptual dimension, transnationalism. Further, this research has added new insights about a recently arrived immigrant group in Toronto. Finally, the study contributes to the social work literature by identifying an emerging field of international social work. It has drawn attention to the fact that in the era of transnationalism, the emergence of a population of migrants whose needs and lives transcend national borders will affect the future of social work research and practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.033 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".