A rapid scoping review of COVID‐19 and vulnerable workers: Intersecting occupational and public health issues
Bibliographic record
Abstract
BACKGROUND: This article reports the results of a rapid scoping review of the literature on COVID-19 transmission risk to workers in essential sectors such as retail, health care, manufacturing, and agriculture, and more particularly the experiences of workers in precarious employment and social situations. METHODS: Following scoping review methods, we included 30 studies that varied in terms of methodology and theoretical approaches. The search included peer-reviewed articles and grey literature published between March and September 2020. RESULTS: Based on the studies reviewed, we found that COVID-19 infection and death rates increased not only with age and comorbidities, but also with discrimination and structural inequities based on racism and sexism. Racial and ethnic minority workers, including migrant workers, are concentrated in high-risk occupations and this concentration is correlated to lower socioeconomic conditions. The COVID-19 pandemic appears in the occupational health and safety spotlight as an exacerbator of already existing socioeconomic inequalities and social inequalities in health, especially in light of the intersection of issues related to racism, ethnic minority status, and sexism. CONCLUSIONS: This review provides early evidence about the limitations of institutions' responses to the pandemic, and their capacity to provide a safe and decent working environment for all workers, regardless of their employment status or the social protections they may enjoy under normal circumstances. It is also important to think about these issues in the postpandemic context, when conditions of precariousness and vulnerability persist and possibly worsen.
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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 | 0.047 | 0.149 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.037 | 0.031 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".