Exposure to COVID-19: is there a disproportionate burden on low-paid jobs in France?
Why this work is in the frame
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Bibliographic record
Abstract
Although a majority of COVID-19 victims are among the elderly, workers holding low-paid jobs in the essential service sectors and those who are more likely to trade their health for economic reasons may be particularly exposed. Our aim is to gather existing data suggesting a disproportionate burden of the epidemic on the lower income categories.We focus on the situation of France, which has been hard hit. Workers highly exposed to the risk of COVID-19 infection are those who routinely have close face-to-face contacts with the public/colleagues, and/or exposure to infectious agents. Prior knowledge on usual working conditions can help us highlight at-risk occupations and related risks outside the work environment during the epidemic. We analysed national data on working conditions (CT2013), exposure to occupational hazards (SUMER2017) and a flash survey conducted during the lockdown.Before the lockdown (mid-March 2020), at least 8.8 million of workers were highly exposed to Covid-19 in France. There were however sharp disparities across occupational groups. As high as 41% of the bottom quarter of earners belonged to the highly exposed group, as opposed to 12% of the top quarter of earners. Apart from health care workers and first responders, other frontline workers with low-pay such as cleaners, personal aids and cashiers are among the most exposed. The situation has yet changed during the lockdown, with teleworking, reduced hours/layoffs, and type and timing of protective measures taken by employers. Lower salary workers have been highly exposed to the risk of COVID-19 infection. They may carry a heavy health burden related to the current crisis, especially when not sufficiently protected. Their occupational risks are further compounded by their transportation and housing conditions, along with comorbidities and access to healthcare. This lays ground to greater spread and severity of the disease among working-age and older working-class adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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 it