Labor and social protection gaps impacting health of non-standard workers: An international study
Bibliographic record
Abstract
Abstract Background Labor regulations and social protection structures are intended to protect workers, but the needs of those in precarious and non-standard employment (NSE) are often missed, which may negatively impact health and well-being. The aim of this research is to document how workers in NSE in six countries - Belgium, Canada, Chile, Spain, Sweden, and the US - with varying policy contexts experience aspects of employment that are linked to health. Methods We employed a mixed methods approach for this study. To understand policy contexts, we analyzed country-level labor regulatory and social protection frameworks using 2019 Organization for Economic Cooperation and Development data. To understand the experiences of workers in NSE, we conducted 250 in-depth interviews with workers at different levels of employment precariousness between January and June 2021. Results Overall, European countries have the most social expenditures and North American countries have the weakest labor market regulations. In all these varying contexts, workers in NSE reported multiple unmet needs, e.g., inadequate paid sick and parental leave and unemployment compensation. These unmet needs occur due to various barriers, including poor enforcement, legal loopholes, or required minimum employment time. Workers’ living accommodations are also affected, as home financing or rental contracts are dependent on permanent employment. In response, they tended to rely disproportionately on individual or family resources for financial and social support rather than on government or employer resources. Conclusions Findings suggested that diverse labor regulatory and welfare regime contexts are unsupportive of workers in NSE due to multiple gaps in policies essential to public health. The shifting of responsibility for key employment and social supports to individuals and their families is likely to increase health inequities for workers in NSE. Key messages • Our study documents multiple policy gaps affecting key employment-related social determinants of health among workers in NSE. • This occurred across diverse labor and social structure contexts in six countries.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".