Critical perspectives on migrants, migration, and COVID-19 vaccination editorial for special issue
Bibliographic record
Abstract
The COVID-19 pandemic has exposed-and exacerbated-major health inequities around the globe including amongst many persons framed as 'migrants whose lives are shaped by discursive legal, political, and social meanings and legal statuses that situate them within local, national, and global hierarchies. This special issue is dedicated to critical analyses of the roll-out of COVID-19 vaccinations in relation to migrants and other minorities associated with migration, and how migrant groups have been considered and neglected by national and global COVID-19 responses. Drawing from work with asylum seekers, internal and international migrants-both documented and undocumented-in countries ranging from Greece, Japan, and India to Thailand and Canada, authors in this special issue apply critical political economic, feminist, and intersectional lenses to examinations of migrants, migration, and COVID-19 vaccinations.
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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".