Humanizing clinical dentistry through a person-centred model
Bibliographic record
Abstract
The clinical approach in dentistry stems from a biomedical model of health that is anchored in positivism. This biomedical model was never explicitly developed or reflected on, but rather implicitly acquired as a product of historical circumstance. A reductionist understanding of health served dentistry well in the past, when health afflictions were mostly acute. Today, however, in the age of chronic illnesses, the current clinical approach is no longer adequate: patients and dentists are both dissatisfied, and there are problems with dental education and dental public health. After a thorough review of the literature, highlighting the current state of the profession, we propose an alternative clinical model upon which updated approaches can be based. We call this model "Person-Centred Dentistry". Our proposed model is rooted on the notion of sharing of power between the dentist and the patient: a sharing of power in the relationship and epistemology. This leads to an expanded understanding of the person and the illness; a co-authoring of treatment plans; and interventions that focus not only on eliminating disease but also on patient needs.
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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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.050 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".