The Canadian Dental Care Plan For Children: A Sustainable Approach?
Bibliographic record
Abstract
This study aims to assess the essential dental services that children should have access to and evaluate whether the newly launched federal Canadian Dental Care Plan (CDCP), in May 2024, meets these needs. A cross-sectional survey was electronically administered in November 2023 to certified Canadian pediatric dentists to determine the normative oral health needs of Canadian children and the services that should be included in the CDCP’s basket of services. As the CDCP released dental services grids, the responses were compared to assess alignment and identify gaps. Of the 297 pediatric dentists surveyed, 109 responded. The respondents were thorough in their approach, selecting a full range of primary, secondary, and tertiary preventive services, and giving equal importance to deciduous and permanent teeth. While their perceptions largely aligned with the CDCP grids, several gaps were also identified, including the absence of services such as mouthguards, preformed zirconia crowns, space maintainers, smoking cessation counseling, oral hygiene instruction, and nutritional counseling. The CDCP dental service grids largely align with pediatric dentists' recommendations for restorative services (secondary and tertiary prevention). However, they fall short in addressing primary prevention, missing an opportunity to build a sustainable oral health care system that addresses not only current needs but also future burdens.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".