Assessment of Surgical Competence in North American Graduate Periodontics Programs: A Survey of Current Practices
Bibliographic record
Abstract
This cross-sectional study was designed to document the methods utilized by North American graduate periodontics programs in assessing their residents' surgical skills. A survey of clinical skills assessment was mailed to directors of all fifty-eight graduate periodontics programs in Canada and the United States. Thirty-four programs (59 percent) responded. The data collected were analyzed using SPSS version 15.0. The results demonstrate that the most common practice for providing feedback and documenting residents' surgical skills in the programs surveyed was daily one-on-one verbal feedback given by an instructor. The next two most commonly reported methods were a standard checklist developed at program level and a combination of a checklist and verbal comments. The majority of the programs reported that the instructors met collectively once per term to evaluate the residents' progress. The results suggest that graduate periodontics programs provide their residents frequent opportunities for daily practice with verbal feedback from instructors. However, assessment strategies identified in other health professions as beneficial in fostering the integration of clinical skills practices are not employed.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".