Report of Recommendations from the National Dental Public Health Workshop, February 10‐12,2002, Bethesda, MD
Bibliographic record
Abstract
A two-and-a-half day workshop was held beginning February 10, 2002, to review the current state of dental public health training in the United States with the aim of creating recommendations that would address identified problems and lead to improvements in the quality of dental public health training. This workshop, held in Bethesda, Maryland, was sponsored by the Health Resources and Services Administration (HRSA) through a contract with the American Association of Public Health Dentistry (AAPHD). Workshop invitees included the program directors of all accredited dental public health residency programs in the United States and Canada, selected dental public health residents, and additional consultants invited based on their expertise in dental public health education. The recommendations have been placed into three categories: training, financing, and workforce development. Along with background and process summaries, these recommendations are reported here.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.015 | 0.010 |
| Insufficient payload (model declined to judge) | 0.037 | 0.025 |
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".