Bibliographic record
Abstract
The author's objective is to summarize and synthesize what is known about the private long-term care insurance market and its impact on public expenditures, policyholders, their families, and providers. Primary data were compiled from national studies and published and nonpublished information from the long-term care insurance industry. The study design was the review and analysis of empirical data. Data were collected from in-person, mail, and telephone interviews, as well as from a review of the literature. The market is growing rapidly in part due to the vast improvements in product design and to federal and state public policies. Growth in the market should result in modest reductions in public long-term care expenditures. Most claimants are satisfied with their policy, but many still do not feel that their needs are being met. Service delivery and provider issues are critical to making money work for disabled persons and insurers will be increasingly called on to help address this issue. The market for long-term care insurance will continue to grow. Over time, this insurance will likely play a more meaningful role in meeting the needs of disabled elders and their families.
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 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 | 0.000 | 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 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".