Graduate orthodontic education in Turkey: the residents' perspective
Bibliographic record
Abstract
The aim of the present study was to explore residents' perceptions of their educational and clinical treatment experiences including the number of clinical cases undertaken, patient completion rates, techniques utilised and the scientific component of Turkish graduate orthodontic programmes. Residents recorded in the list of Turkish Orthodontic Society were sent an e-mail to participate in a survey containing 46 multiple-choice questions and ten one-line answers. An e-mail with a personalised online link was sent to a total of 227 residents throughout the Turkey. Data were categorised, and basic statistics including chi-square comparative analyses were performed. A total of 136 (response rate of 59.91%) residents completed the survey. The majority of residents (58.08%) were either 'very satisfied' or 'satisfied' with their programme. Respondents said they have just the right amount of formal didactic teaching sessions or dedicated and protected academic time. Most residents (69.11%) indicated their programme offers training in numerous philosophies; whilst 97.79% said they have sufficient clinically based training and 42.64% said they have sufficient research-based training. Overall, residents in the Turkey are satisfied with their orthodontic programme. They receive comprehensive training with the opportunity to start and complete a significant number of their patients. The survey findings suggest that orthodontic programmes in Turkey are deficient in providing care to underserviced populations and disabled patients. Programmes could improve the opportunity for residents to treat patients requiring interdisciplinary treatment.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".