Sustaining the Private Sponsorship of Resettled Refugees in Canada
Bibliographic record
Abstract
For more than 40 years, groups of Canadian residents have raised funds and offered their time and energy to support over 325,000 refugee newcomers to Canada through the Private Sponsorship of Refugees Program. In 2020, targets for private refugee sponsorship in the Canadian context were double the number of government-assisted refugees. Private sponsorship is therefore an important focus of analysis in relation to refugee resettlement, representing a complementary pathway to refugee protection through civil society mobilization. Yet, little research to-date has focused on private sponsorship. Based on an original qualitative study, this paper probes how voluntary sponsorship has been sustained over decades, despite the high personal and financial costs it entails, by analyzing the insights of those who have experienced sponsorship: former refugees who came through the program, long-term sponsors, key informants, and other community leaders. The authors argue that private refugee sponsorship is a community practice , a routine action that is part of a collective commitment, a way of connecting local community actions to global politics of injustice and displacement. Furthermore, refugee newcomers who land in Canada as permanent residents become part of the communities and society in which they stay. Having left family members behind in refugee camps and cities of refuge, many become sponsors themselves. This phenomenon of ‘family linked’ sponsorship is a defining and sustaining feature of the program, motivating family members in Canada to team up with seasoned sponsors to ‘do more’. Our data show that sponsorship occurs across scales—linking local sites in Canada to countries where human atrocities are common and neighboring states that host those who flee. Sponsorship connects people in various communities across the world, and these transnational links are important to understanding the sustainability of sponsorship over time in Canada. Our research pays attention to the narratives of sponsors and those they support with the objective of documenting the momentous contribution of this complementary, and expanding, pathway for refugee protection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".