What non-clinical factors influence the general dentist–specialist relationship in Canada?
Bibliographic record
Abstract
BACKGROUND: The general dentist-specialist relationship is important for effective patient care and the professional environment. This study explores the non-clinical factors that may influence the general dentist-specialist relationship in Canada. METHODS: A cross-sectional web-based survey of a sample of general dentists across Canada was conducted (N ≈ 11,300). The survey collected information on practitioner (e.g., age, gender, years of practice) and practice (e.g., location, ownership) factors. Two outcomes were assessed: not perceiving specialists as completely collegial and perceiving competitive pressure from specialists. Binary and multivariable logistic regression analysis was conducted. RESULTS: A total of 1328 general dentists responded, yielding a response rate of 11.7%. The strongest associations for perceiving specialists as not completely collegial include being a practice owner (OR = 2.15, 95% CI 1.23, 3.74), working in two or more practices (OR = 1.69, 95% CI 1.07, 2.65), practicing in a small population center (OR = 0.46, 95% CI 0.22, 0.94), and contributing equally to the household income (OR = 0.47, 95% CI 0.26, 0.84). The strongest associations with perceiving medium/large competitive pressure from specialists include having a general practice residency or advanced education in general dentistry (OR = 2.00, 95% CI 1.17, 3.41) and having specialists in close proximity to the practice (OR = 2.52, 95% CI 1.12, 5.69). CONCLUSION: Practitioner and practice factors, mostly related to business and dental care market dynamics, are associated with the potential for strained relationships between general dentists and specialists in Canada. This study points to the need for dental professional organizations to openly discuss the current state of the dental care market, as it has important implications for the profession.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".