Nurturing Refugee Hospitality: A Case Study of Canada's Private Sponsorship of Refugees Program and Its Implications for South Korea
Bibliographic record
Abstract
The global refugee crisis, intensified by protracted wars and conflicts, increasingly demands responsibility from hosting countries. However, South Korea (Korea) has maintained a closed stance on refugee intake, with an annual average of only 48 refugees accepted since implementing its refugee law in 1994. Such responses from hosting countries are inadequate for addressing the refugee crisis. This research seeks out strategies to enhance inclusivity and hospitality towards refugees in closed hosting countries such as Korea. To that end, Canada’s Private Sponsorship of Refugees Program (PSRP) case will be examined. Over the past 40 years, Canada’s PSRP and its civil organizations have successfully resettled over 300,000 refugees, fostering a welcoming climate. This may provide implications for Korean civil leaders and local actors to apply in their context. This research will focus on finding social conditions and motivations that enabled the private sponsors’ involvement in refugee protection and allowed their sustainable action. Qualitative secondary analysis that uses data from published research and media will be utilized. The data comprises interviews and surveys, including responses from over 700 sponsors. The findings indicate that the legal structure of the PSRP, the government’s leadership in promoting the program, and the roles of media and civil organizations in encouraging public participation shaped social conditions that streamlined Canadian citizens’ engagement. Under the circumstances, the individuals were motivated by media, ethics and compassion, refugee experiences, desire for political response, and family concerns, while emotional rewards and their community’s encouragement drove some private sponsors to engage continually. This research could contribute to finding effective ways for Korean civil leaders and local actors to nurture a culture of peace, including values of understanding, tolerance, and social cohesion, in their society. Additionally, this research provides actionable strategies for them to emphasize community engagement as a key factor for fostering refugee hospitality.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.049 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".