(Released 3/2005) Health Insurance Coverage: Estimates from the National Health Interview Survey, January–September 2004
Bibliographic record
Abstract
Two additional questions were added to the health insurance section of the National Health Interview Survey (NHIS) beginning with quarter 3 of 2004 to improve the accuracy of the estimates. Therefore, some estimates reported here are not directly comparable with estimates previously published. From January through September 2004, 41.6 million persons of all ages (14.5%) were uninsured at the time of the interview, 51.0 million (17.7%) had been uninsured for at least part of the year prior to the interview, and 28.9 million (10.1%) had been uninsured for more than a year at the time of the interview. For children under age 18 years, the percentage uninsured at the time of the interview was 9.2 % in the first three quarters of 2004, continuing the decline observed since 1997. The percentage of children uninsured for more than a year has continued to decrease since 1997. From January through September 2004, 69.6 % of poor children and 44.6 % of near poor children were covered by a public health plan at the time of interview. From 1999 through 2003, the estimates of public coverage increased among children, but the largest increase was seen among near poor children. During the same period, there was a decreasing trend in the percentage of poor and near poor children with private coverage. However, the differences in the estimates of private or public coverage between 2003 and the first 9 months of 2004 for children were not statistically significant. During the first 9 months of 2004, more than 58 % of currently unemployed adults and nearly 21% of employed adults aged 18–64 years had been uninsured for at least part of the past year, and 32.8 % of currently unemployed adults and 12.6 % of employed adults had been uninsured for more than a year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.041 |
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".