The Number of Americans without Health Insurance Rose in 2001 and Continued to Rise in 2002
Bibliographic record
Abstract
Data from the Census Bureau and the Centers for Disease Control and Prevention indicate that the number of uninsured Americans rose in 2001and in the first quarter of 2002. The main reason insurance coverage fell was a drop-off in employer-sponsored insurance for workers and their dependents. This reduction was triggered by rising unemployment levels and rising health insurance premiums, which made it more difficult for employers to offer insurance or for workers to afford it. The downturn in private coverage was partially offset by increased enrollment in Medicaid and the State Children's Health Insurance Program (SCHIP). About two million mor e children and one million more adults would have been uninsured had it not been for the growth in these programs. Funding for the public programs is, however, threatened by budget shortfalls affecting most states, which administer these programs. Many states have cut their Medicaid programs and are planning further cutbacks. Increasing federal assistance to states and their Medicaid programs could help protect insurance coverage for low-income people during the current economic slowdown. Future SCHIP enrollment could drop sharply because of a shortage of federal funds, and Congress could take steps to bolster SCHIP funding.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".