1.4 Research and the dental student
Bibliographic record
Abstract
There has been significant concern that the dental curriculum and system of clinical education, in particular, is not designed to take advantage of the explosion in knowledge in biomedical science and its application to the health of the public. Although there are some examples of innovations in dental education on a global scale that have the capacity to increase the assimilation of basic and clinical knowledge, most of the dental education models are mired in the traditional '2 + 2' approach to education. This can be seen in North America and the European '2 + 3' model or the stomatological '4 + 2' approach. In each of these systems, the basic and behavioural science courses continue to be perceived as hurdles over which students must leap in order to reach the clinical programmes where there is little opportunity to use basic science information to advance patient care and treatment. Examples of issues that are not well represented include: innovations in imaging; diagnosis; bio-materials; science-based approaches to clinical practice; novel approaches to therapeutics; interactions between the oral, dental and craniofacial complex and systemic health and disorders; the role of oral infections and systemic disease; the increasing appreciation of chronic diseases and disorders such as osteoporosis and diabetes that affect oral tissues; the promise of bioengineering, tissue engineering and biomimetics; the potential use of saliva as a diagnostic tool; the understanding of oral complications of cancer treatment; the treatments of HIV/AIDS diseases and hepatitis; the use of dental and dental hygiene staff on health-care teams to deal with issues such as birth defects, orofacial trauma, head and neck cancer, chronic pain management and so on. There seems to be an excessive emphasis on restorative dentistry and, to a lesser extent, on the more biological approaches to diagnosis, prevention and therapeutics. This continued lack of integration of basic and clinical sciences in the curriculum continues to foster a dental workforce that is highly technically competent to provide specific clinical services but poorly equipped to evaluate and implement new biological approaches to diagnosis, therapeutics and intervention. Unfortunately, after many attempts by organized dental symposia aimed at the integration of basic and clinical sciences, there has been little discernible curricular change. It appears that there is an opportunity through this global congress to identify the best practices in the various global curricula that could change this paradigm in dental education and lead us toward the education of a more scientifically orientated practitioner-one who can take advantage of innovations in new and emerging technologies in their application to patient care. It is the challenge of this section to try to ascertain the best method or methods by which dental education promotes research to the dental student and what research represents in terms of critical thinking and evidence-based approaches to dental education and clinical practice.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.078 | 0.028 |
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".