Bibliographic record
Abstract
In a recent CDA member information bulletin entitled “Fluoride and Dentistry,” the following question was posed: “If fluoride is available from many sources, and the prevalence of dental fluorosis among children is increasing, why does CDA continue to support water fluoridation?” In this paper, we take a brief look at this question from an ethical perspective.\nFormal ethical reflection and analysis have become expected components of decision making for all health professionals. Ethics is the branch of philosophy that explores value-laden decision making and conduct. Fair and respectful health policy and practice require an understanding of the values that underlie our choices. Decisions made in clinical practice and in public health policy should be a reflection of the values and beliefs of individual decision makers and of society as a whole. Ethically sound health care policy-making requires balancing the potential benefits and harms of all alternatives. Assessing the ethical validity of the CDA policy on water fluoridation therefore requires a consideration of the potential benefits and harms of water fluoridation.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".