Is there a social justice to dentistry’s social contract?
Bibliographic record
Abstract
How should the dental profession of the 21st century frame its interactions with the society it is tasked to care for? What has this relationship looked like in the past, and what does it look like today? In this article, we examine these and other issues through the framework of the social contract, with a focus on exploring how social justice fits within the transaction of duties between the dental profession and society. We begin by describing the social contract and how this is uniquely defined within the context of dentistry; specifically, how the context of dentistry as, in part, an aesthetically driven discipline, impacts the social contract. We then consider how the nature of the profession's relationship with society, and the orientation by which it provides its services (which is sometimes critically unclear in its definitional terms), impacts the profession's contribution to ensuring social justice in oral health and oral healthcare. Through examining the nature of how the social contract has shifted (for example, by the attenuation of professional monopolies), we also ask whether this is evidence of a loss of confidence in the dental profession as an altruistic institution. We end by suggesting that the dental profession must engage with the tenets of social justice within the social contract. Failure to do so is likely to lead to erosion of dentistry as a high-status profession and societal willingness to seek solutions to oral health needs from other professional and non-professional sources.
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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 | 0.038 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.120 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".