Canadian radiology workforce demographics: Results from a national survey
Bibliographic record
Abstract
Rationale and objective: Demographic data collected about Canadian radiologists and trainees has been limited primarily to binary gender and geographic location. The purpose of this study was to investigate: (1) demographic characteristics of Canadian radiologists and trainees; (2) types of diversity important to radiologists; (3) relationship of radiologist demographics to practice characteristics; and (4) relationship of radiologist demographics to years in practice, (YIP). Materials and methods: French and English surveys were distributed via email through radiology associations and social media. Frequency counts of demographic variables were calculated, and chi-square and Fisher's Exact tests were performed to explore the relationships between demographic characteristics and role. Results: 611 individuals responded to the survey. 573 respondents were included in the analysis. 454 (78.8%) were practicing radiologists and 119 (20.7%) were residents/fellows. Half identified as women (50.4%). English was the primary language for most respondents. There was an association between role and sexual orientation (p = 0.02), visible minority (χ2 = 4.79, p < 0.05), religion (χ2 = 4.11, p < 0.05), and having children (χ2 = 136.65, p < 0.05). For radiologists, being a visible minority (χ2 = 11.59, p < 0.05) and age (χ2 = 56.3, p < 0.05) were associated with academic rank while gender (χ2 = 3.83, p < 0.05) and age (χ2 = 13.74, p < 0.05) were related to part-/full-time status. Less women, visible minorities, and women with children had been in practice for long. Discussion: This study represents a comprehensive analysis of Canadian radiology demographics. Results suggest there is increasing diversity among trainees; however, significant demographic underrepresentation compared to the diversity of Canada exists.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".