A protective rung on the ladder? How past and current social status shaped changes in health during COVID-19
Bibliographic record
Abstract
An emerging body of work has started to document population health consequences of the social and economic transformations during the COVID-19 pandemic. We consider an individual's relative social position in the stratification system-subjective social status (SSS)-and assess how past (childhood) and current SSS predict change in self-rated health during the pandemic. Using two waves of data from the Canadian Quality of Work and Economic Life Study, we follow respondents between the onset of lockdown measures in March and May of 2020 (N = 1886). Drawing from the life course perspective and stress process model, we find that lower current SSS predicts a greater likelihood of being in stable poor health and reporting declining health. Lower past SSS predicts a higher chance of being in stable poor health indirectly through current SSS. And lower cumulative SSS that sums both past and present SSS also predicts stable poor health, while perceived upward mobility over time is associated with stable good health. This robust relationship between SSS and health in such a short time period of two months at the start of the COVID-19 pandemic provides an important glimpse into the influence that SSS has on population health.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".