Work Requirements and Medicaid Disenrollment in Arkansas, Kentucky, Louisiana, and Texas, 2018
Bibliographic record
Abstract
Objectives. To identify risk factors for Medicaid disenrollment after the implementation of Arkansas’s work requirements. Methods. Using a 2018 telephone survey of 1208 low-income adults aged 30 to 49 years in Arkansas (expansion state with work requirements implemented in June 2018), Kentucky (expansion state with proposed work requirements blocked by courts), Louisiana (expansion state without work requirements), and Texas (nonexpansion state), we assessed Medicaid disenrollment rates among the age group targeted by Arkansas’s policy. Results. The Medicaid disenrollment rate was highest in Texas (12.8%), followed by Arkansas (10.5%), Kentucky (5.8%), and Louisiana (2.8%). Over half of those who disenrolled in Texas and Arkansas became uninsured, compared with less than a quarter in Kentucky and Louisiana. In multivariate models, Arkansas had significantly higher disenrollment compared with the 3 comparison states; men and non-Hispanic Whites experienced higher disenrollment than women and racial minorities. In Arkansas, having a chronic condition was associated with higher disenrollment. Conclusions. As states debate work requirements and Medicaid reforms, our findings provide insights for policymakers about which populations may be most vulnerable to losing Medicaid coverage.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".