Health Benefits In 2023: Premiums Increase With Inflation And Employer Coverage In The Wake Of <i>Dobbs</i>
Bibliographic record
Abstract
In 2023 the average annual premium for employer-sponsored family health insurance coverage was $23,968—an increase of $1,505 (7 percent) from 2022. Both single and family premiums increased faster in 2023 than in 2022, in a period of generally high inflation throughout the US economy. On average, covered workers contributed 17 percent ($1,401) of the cost of single coverage and 29 percent ($6,575) of the cost of family coverage. When compared to employers’ perceptions of the number of primary care providers in their networks, a smaller share of employers believed that their provider networks had a sufficient number of mental health and substance abuse providers to provide timely access to services. One-quarter of employers indicated that their employees had a “high” level of concern with the level of cost sharing required by their plans. When asked about abortion coverage in the wake of the Supreme Court Dobbs decision, almost a third of large employers reported that their largest plan covered abortion in most or all circumstances.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".