Health Spending Growth At A Historic Low In 2008
Bibliographic record
Abstract
In 2008, U.S. health care spending growth slowed to 4.4 percent--the slowest rate of growth over the past forty-eight years. The deceleration was broadly based for nearly all payers and health care goods and services, as growth in both price and nonprice factors slowed amid the recession. Despite the slowdown, national health spending reached $2.3 trillion, or $7,681 per person, and the health care portion of gross domestic product (GDP) grew from 15.9 percent in 2007 to 16.2 percent in 2008. These developments reflect the general pattern that larger increases in the health spending share of GDP generally occur during or just after periods of economic recession. Despite the overall slowdown in national health spending growth, increases in this spending continue to outpace growth in the resources available to pay for it.
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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 | 0.001 | 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 | 0.001 |
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 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".