The Fate of Sub-Saharan Migrants and Refugees
Bibliographic record
Abstract
Abstract Before the COVID-19 pandemic, migrants, refugees, and asylum seekers were considered some of the most socially vulnerable groups among other sub-population groups. There is a ponderance of evidence indicating that during the COVID-19 era: (1) their social vulnerabilities were underpinned by not-so-new but re-emerging and adapting pre-existing social drivers such as xenophobic stigmas and nationalism; (2) weaponizing measures used to fight the pandemic such as social distancing to alienate these groups socially—social exclusion; and (3) their social vulnerabilities were exacerbated during the COVID-19 pandemic directly through the impact of the viral infections (loss of loved ones and social support) and indirectly through their audacious exclusion during the execution of different measures to buffer the socioeconomic impact of the pandemic. Using data from a recent qualitative study, we illustrate how the absence or ineffectiveness of social welfare systems failed these vulnerable groups during the COVID-19 pandemic, negatively impacting all aspects of their lives.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 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".