Community Sponsorship and Complementary Pathways: Global Movements for Resettling Refugees Driven by Local Actors
Bibliographic record
Abstract
Abstract The ongoing global displacement emergency characterised by increasing numbers of forced migrants needing refuge has prompted the exploration of alternative solutions to traditional refugee resettlement programmes. Complementary Pathways and Community Sponsorship have emerged as innovative approaches to refugee resettlement which often involves partnership between the state and civil society and potentially the private sector. These initiatives build on years of experience from Canada in the shape of their Private Sponsorship Programme. This paper contributes to the study of these initiatives as they emerge outside of Canada by establishing the state of knowledge on Complementary Pathways and Community Sponsorship. Through a systematic literature review of peer-reviewed research on these programmes, we set out what is known, identify research gaps and outline a future research agenda. The review describes and synthesises works written in English, French, Portuguese, Spanish and Italian, focussing on initiatives introduced outside Canada published post-2015 refugee ‘emergency’. The paper ends by setting out the ways in which the contributions which follow attend to some of the gaps in knowledge identified in the review thereby setting the foundations for this special issue.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".