Characteristics of Canadian physicians and their associations with practice patterns: a scoping review
Bibliographic record
Abstract
Background: Physician characteristics such as education and sociodemographic attributes are associated with particular practice patterns, such as practice in rural settings. Understanding the Canadian context of such associations can inform medical school recruitment and health workforce decision-making. Objective: The objective of this scoping review was to report the nature and extent of the literature on associations between characteristics of physicians in Canada and physicians' practice patterns. Eligibility criteria: We included studies reporting associations between 1) the education or sociodemographic attributes of practicing physicians or residents in Canada and 2) practice patterns, including career choice, practice setting, and populations served. Methods: We searched five electronic databases (MEDLINE (R) ALL, Embase, ERIC, Education Source and Scopus) for quantitative primary studies and reviewed reference lists of included studies for additional studies. Data were extracted using a standardized data charting form. Results: Our search yielded 80 studies. Sixty-two examined education, evenly divided between undergraduate and postgraduate. Fifty-eight examined physicians' attributes, most focusing on sex/gender. The majority of studies focused on the outcome of practice setting. We found no studies examining race/ethnicity or socioeconomic status. Conclusion: Many studies in our review found positive associations between (i) rural training or rural background and rural practice setting and (ii) location of training or physicians' origin and practice in that location, consistent with previous literature. Associations for sex/gender were mixed, suggesting it may be a less useful target for workforce planning or recruitment aiming to address gaps in health care provision. More research is needed on the association of characteristics, particularly race/ethnicity and socioeconomic status, with career choice and populations served.
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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 | 0.014 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.031 | 0.062 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".