The Affordability Of Individual-Market Health Insurance In California Under The American Rescue Plan Act, 2021
Bibliographic record
Abstract
In 2021 the American Rescue Plan Act increased premium subsidies for people purchasing insurance from the Affordable Care Act Marketplaces and provided zero-premium Marketplace plans that covered 94 percent of medical care costs (silver 94 plans) to recipients of unemployment compensation. Using data on adult enrollees in on- and off-Marketplace individual plans in California in 2021, we found that 41 percent reported incomes at or below 400 percent of the federal poverty level and that 39 percent reported living in households receiving unemployment compensation. Overall, 72 percent of enrollees reported having no difficulty paying premiums, and 76 percent reported that out-of-pocket expenses did not affect their seeking of medical care. The majority of enrollees eligible for plans with cost-sharing subsidies were enrolled in Marketplace silver plans (56-58 percent). Many of these enrollees, however, may have missed opportunities for premium or cost-sharing subsidies: 6-8 percent enrolled in off-Marketplace plans and were more likely to have difficulty paying premiums than those in Marketplace silver plans, and more than one-quarter enrolled in Marketplace bronze plans and were more likely to delay care because of cost than those in Marketplace silver plans. In the coming era of expanded Marketplace subsidies under the Inflation Reduction Act of 2022, helping consumers identify high-value and subsidy-eligible plans could mitigate remaining affordability problems.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".