Offerings for Foreign-Trained Dentists pursuing unrestricted licensure in the United States
Bibliographic record
Abstract
Background:While about 50% of applicants are accepted into dental schools, acceptance rates to Internationally Trained Dentist Programmes(ITDPs) are estimated to be about 2% making it one of the most competitive dental programmes in the United States. Aim:This paper provides a structured review of dental school websites in order to document and distinguish training opportunities for foreign trained dentists that do and do not lead to unrestricted licensure in the United States (U.S.) Materials and Methods: Three independent reviewers conducted a manual search of the US dental school website and a fourth served as arbiter. University of Michigan Medical School’s Committee on Human Research reviewed the study and deemed that no IRB oversight was necessary for this review. Results: Only 40 US dental schools offered Internationally Trained Dentist Programmes (ITDPs) for foreign trained dentists. Additionally, there were 32 non-clinical, non- Commission on Dental Accreditation (CODA) accredited programmes that do not lead to licensure. Conclusions: Our study found that less than 60% of dental schools offer an offered Internationally Trained Dentist Programme (ITDP) but several offer observerships/externships to foreign trained dentists that do not lead to licensure. Both of these programmes are costly and timely, therefore, schools with these programmes; observerships/externships should consider expanding the number of seats in their Internationally Trained Dentist Programme (ITDPs) or if they do not have an Internationally Trained Dentist Programme (ITDP) but offer an observerships/externship programme, then possibly creating one. KeyWords: Academic recruitment; Professional student; Licensure and certification.
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 | 0.012 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".