A discourse on the nature of dental hygiene knowledge and knowing
Bibliographic record
Abstract
OBJECTIVE: Historically, dental hygiene has adopted theory and research from other health disciplines, without adequately modifying these concepts to reflect the unique dental hygiene practice context, leaving dental hygiene's research and theory base underdeveloped. Dental hygiene has yet to articulate its epistemological assumptions--the nature, scope and object of dental hygiene knowledge--or to fully describe the patterns of knowing that are brought to practice. METHODS: This paper uses a method of inquiry from philosophy to begin the discourse about dental hygiene ways of knowing. In nursing, Carper identified four fundamental patterns of knowing: empirics or the science of nursing; aesthetics or the art of nursing; personal knowledge and ethical or moral knowledge. These patterns were used to explore this concept within dental hygiene. RESULTS: There is more to the nature of dental hygiene knowledge and knowing than rote application of technique-related or research-based information in practice, including judgements about when and how to use different types of information that are used. Currently, empirical forms of knowledge seem to be disproportionately valued, yet evidence was found for all of Carper's four patterns of knowing. CONCLUSIONS: Carper's work on patterns of knowing in nursing provided a useful framework to initiate the discourse on ways of knowing in dental hygiene. These results are submitted for others to challenge, refine and extend, for continuing the discussion. Dental hygiene leaders and scholars need to engage in discourse about extending the epistemological assumptions to reflect reality.
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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 | 0.033 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.020 | 0.097 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".