Public preferences for seeking publicly financed dental care and professional preferences for structuring it
Bibliographic record
Abstract
OBJECTIVES: To test the hypotheses that socially marginalised Canadians are more likely to prefer seeking dental care in a public rather than private setting, and that Canadian dentists are more likely to prefer public dental care plans that approximate private insurance processes. METHODS: Data on public opinion were collected through a weekly national omnibus survey based on random digit dialling and telephone interview technology (n = 1005, >18 years). Data on professional opinion were collected through a national mail-out survey of a random selection of Canadian dentists (n = 2219, response rate = 45.8%). Dental and socio-demographic data were collected for the public, as were professional demographic data for dentists. Descriptive and basic regression analyses were undertaken. RESULTS: The majority of Canadians surveyed, 66.4%, prefer to seek dental care in a private setting, 19% in a community clinic, and 7.6% in a dental school; those that are younger and of lowest incomes are most likely to prefer seeking dental care in a public setting. Most Canadian dentists, 80.9%, believe that governments should be involved in dental care, yet only 46% believe this role should include direct delivery. A third of dentists have also reduced the amount of publicly insured patients in their practice. Canadian dentists are more likely to prefer those public plans that most closely reflect private insurance mechanisms. CONCLUSION: There appears to be a policy disconnect between the preferences of those populations where governmental involvement is most warranted, and the current mechanisms for financing and delivering dental care in Canada. By concentrating almost exclusively on third-party-type financing and indirect delivery, public dental care policy may not be adequately responding to those most in need, especially in an environment where dentists are largely dissatisfied with public plans.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".