A Micro-Level Model of Employment Relations and Health Inequalities
Bibliographic record
Abstract
Theoretical models are a way of visualizing, in context, the many factors that contribute to inequalities in health. This article presents a model showing the micro-level pathways relating employment and working conditions to health inequalities. A first important (indirect) pathway runs through the unequal distribution of harmful working conditions. Both employment and working conditions tend to be unequally distributed along the same social axes: social class, gender, ethnicity/race, immigration/migration status, territory, and so forth. Underlying mechanisms are exploitation, domination, and discrimination. Material deprivation and economic inequalities constitute a second direct pathway linking (nonstandard) employment conditions to health inequalities. In a third pathway, employment conditions may have an important effect on health inequalities via several psychosocial, behavioral, and physiopathological pathways. Although these several pathways are separated for analytical purposes, they are largely intertwined and, ideally, should be studied in an integrated way. The theoretical model presented in this article serves three main purposes: providing analytical clarity for organizing scientific data, encouraging further observation and causal testing, and identifying policy entry points.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".