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
Social inequality in access to oral health care is a feature of countries with predominantly privately funded markets for dental services. Private markets for health care have inherent inefficiencies whereby sick and poor people have restricted access compared to their healthy and more affluent compatriots. In the future, access to dental care may worsen as trends in demography, disease and development come to bear on national oral healthcare systems. However, increasing public subsidies for the poor may not increase their access unless availability issues are resolved. Further, increasing public funding runs counter to policies that feature less government involvement in the economy, tax policy on private insurance premiums, tax reductions and, in some instances, free-trade agreements. We discuss these issues and provide international examples to illustrate the consequences of the differing public policies in oral health care. Subsidization of the poor by inclusion of dental care in social health insurance models appears to offer the most potential for equitable access. We further suggest that nations need to develop national systems capable of the surveillance of disease and human resources, and of the monitoring of appropriateness and efficiency of their oral healthcare delivery systems.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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