Psychiatric disorders and labor market outcomes: evidence from the National Latino and Asian American Study
Bibliographic record
Abstract
This paper investigates to what extent psychiatric disorders and mental distress affect labor market outcomes in two rapidly growing populations that have not been studied to date-ethnic minorities of Latino and Asian descent, most of whom are immigrants. Using data from the National Latino and Asian American Study (NLAAS), we examine the labor market effects of meeting diagnostic criteria for any psychiatric disorder in the past 12 months as well as the effects of psychiatric distress in the past year. The labor market outcomes analyzed are current employment status, the number of weeks worked in the past year among those who are employed, and having at least one work absence in the past month among those who are employed. Among Latinos, psychiatric disorders and mental distress are associated with detrimental effects on employment and absenteeism, similar to effects found in previous analyses of mostly white, American born populations. Among Asians, we find more mixed evidence that psychiatric disorders and mental distress detract from labor market outcomes. Our findings suggest that reducing disparities and expanding access to effective treatment may have significant labor market benefits-not just for majority populations, as has been demonstrated, but also for Asians and Latinos.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".