The Substance of Solidarity: What the Response to the COVID-19 Pandemic Says About the Global Refugee Regime
Bibliographic record
Abstract
The European migrant crisis of 2015 brought to light the urgent need for solidarity and responsibility-sharing in dealing with large influxes of people fleeing war, conflict and persecution. This spirit was captured in two subsequent international agreements: the Global Compact on Refugees (GCR) (2018) and the Global Compact for Safe and Orderly Migration (GCM) (2018). In the midst of a very different kind of crisis - the global COVID-19 pandemic - the need for solidarity and responsibility-sharing is all the more imperative as COVID-19 has become a 'risk multiplier' for asylum seekers, compounding existing drivers. By examining how Western nation states in the global North have responded to asylum seekers during the pandemic against the backdrop of existing international refugee law, practice, and policy, this essay seeks to evaluate the normative potential of the GCR and the GCM for the entrenchment of the principle of solidarity. Employing the theoretical framework of governmentality, it argues that despite the rhetoric of responsibility-sharing, the reactions of Western nation states reflect an existing trend toward exclusionary impulses, with countries reflexively reverting to patterns of state-centric, insular protectionism. Taking these issues into consideration, the essay goes on to focus on Canada's response to the COVID-19 pandemic in light of its proximity to and relationship with the United States to illustrate how biopower is being deployed to exclude in line with neoliberal rationalities, even in a country that is usually heralded as a beacon of humanitarianism. The essay concludes with a guarded diagnosis that warns of the potential for an international protection crisis should civil society fail to challenge prevailing biopolitics. Keywords: COVID-19, Asylum Seekers, Refugees, Solidarity, Responsibility-sharing, Governmentality, Biopower, Neoliberal, Canada, United States
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.062 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".