Facilitating Mobility Through Migration as Humanitarian Protection: Building on Lessons Learned from the North American and European Policies Regarding Haiti and Syria
Bibliographic record
Abstract
This paper addresses the contribution of three major humanitarian assistance donors, Canada, the United States of America (US), and the European Union (EU), to humanitarian diplomacy, and ways to articulate migration policy and humanitarian policy in the action of these three actors to facilitate mobility. Building on lessons learned from the Syrian and Haitian humanitarian crisis-related migration, this study asks: while conflicts, natural disasters and other calamities increase humanitarian needs, based on the spirit of the Global Compact for Migration, how and to what extent could Canada, the US and the EU, as major humanitarian donors, better promote humanitarian action in coherence with their migration policy and make humanitarian migration a means to protect the rights of individuals affected by the complex humanitarian crisis? The paper argues that, while being of soft law character, the Global Compact for Migration provides for a promising intersection between migration and humanitarian crisis to facilitate mobility through migration as humanitarian protection, by articulating norms and policies that lead, otherwise, to the instrumentalization of humanitarian assistance. Such an articulation should reconcile humanitarian considerations and migration policy in the context of multidimensional armed conflicts and natural-disaster-made humanitarian crises. In this regard, practices in the Haitian and Syrian contexts show challenges to the proposed articulation given the primacy of state interests, and discretion that governs in the field. This results in a tension between an enthusiastic narrative on humanitarian assistance and a restrictive approach to humanitarian-immigration admission, leading to contradictory practices. Indeed, as illustrated by actions of the US and the EU in the Syrian and Haitian crises, state discretion in migration policy and law, amalgamation surrounding migration, the fight against terrorism, populism, and xenophobia show politicization of international protection and instrumentalization of humanitarian assistance, that have led to the externalization of migration policy. Thus, new pathways in states’ domestic law and policy, such as redefining family reunification and increasing involvement of migrants-focused organizations in sponsorship, would help reconcile State interests, humanitarian assistance, and migration as humanitarian protection.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.028 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".