Socioeconomic Status and Mental Illness
Bibliographic record
Abstract
Abstract Socioeconomic status (SES) is a complex construct that is commonly used to understand mental health inequalities. SES refers to the social relations that determine what structural locations individuals or groups hold within society, which in turn influence the exposures, resources, and susceptibilities that produce mental health inequalities. The association between SES and mental health is one of the most firmly established patterns in psychiatric epidemiology – the most privileged and deprived tend to experience the best and worst mental health outcomes, respectively. Three major sociological traditions are relevant to understanding the causal processes through which SES determines the likelihood of developing a mental health disorder. The first tradition conceptualizes SES in terms of social stratification, or the ranking of individuals into groups based on shared socioeconomic conditions. The second uses a neo‐Weberian perspective, and defines SES as being determined by social closure and opportunity hoarding, or the processes through which privileged groups restrict access to economic resources and opportunities while excluding others. The third reflects a neo‐Marxist approach, and identifies SES with domination and exploitation, or the ability of owners of productive resources to control and benefit from the labor of workers.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".