The dental therapist movement in the United States: A critique of current trends
Bibliographic record
Abstract
Dental therapists are members of the oral health workforce in over 50 countries in the world typically caring for children in publically funded school-based programs. A movement has developed in the United States to introduce dental therapists to the oral health workforce in an attempt to improve access to care and to reduce disparities in oral health. This article critiques trends in the United States movement in the context of the history and success of dental therapists practicing internationally. While supporting the dental therapist movement, we challenge: a) the use of dental therapists treating adults, versus focusing on children; b) the use of dental therapists in the private versus the public/not-for-profit sector; and c) requirements that a dental therapist must also be credentialed as a dental hygienist.
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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 | 0.024 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.025 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".