Comprehensive Dental Care in Canada: The Choice Between Denticaid and Denticare
Bibliographic record
Abstract
A healthy mouth is an essential ingredient for overall good health, but a Canadian’s access to comprehensive dental care is dependent on their ability to attain private insurance. This paper seeks to estimate the gross and net total cost of two policy options for introducing comprehensive dental care into Canadian Medicare. Using a micro-costing approach for estimating the annual clinical costs, and an average-costing approach for annual administrative expenses, this paper estimated the total cost of universal first dollar dental coverage (denticare) and public dental insurance for children and uninsured adults in Canada (denticade). If the denticare option was implemented in the year 2019, the gross total public-sector cost would to be roughly $15.68 billion. This would replace the current $1.02 billion spent on existing public health dentistry programs and $6.27 billion spend on public employee’s dental plans. The total cost could be further offset by the inclusion of income-tiered premiums set at a maximum rate below private insurance provider prices. The net total cost of denticare would then be an aggregate decrease in public spending by $127.08 million. If the denticade option was implemented in the year 2019, the gross total public-sector cost would to be roughly $8.43 billion. This would replace the current $1.02 billion spent on existing public health dentistry programs but would not replace spending on public employee’s dental plans. The total cost could be further offset by the inclusion of income-tiered premiums and copayments. The net total cost of denticade would an aggregate increase in public spending by $1.41 billion. The results of this costing analysis demonstrate that by pursuing the universal first-dollar coverage option, Canadians taxpayers could see a reduction in tax-based spending and a considerable decrease in dental premiums changed than if the denticade approach was pursued.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".