National Health Care Spending In 2018: Growth Driven By Accelerations In Medicare And Private Insurance Spending
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
US health care spending increased 4.6 percent to reach $3.6 trillion in 2018, a faster growth rate than the rate of 4.2 percent in 2017 but the same rate as in 2016. The share of the economy devoted to health care spending declined to 17.7 percent in 2018, compared to 17.9 percent in 2017. The 0.4-percentage-point acceleration in overall growth in 2018 was driven by faster growth in both private health insurance and Medicare, which were influenced by the reinstatement of the health insurance tax. For personal health care spending (which accounted for 84 percent of national health care spending), growth in 2018 remained unchanged from 2017 at 4.1 percent. The total number of uninsured people increased by 1.0 million for the second year in a row, to reach 30.7 million in 2018.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it