Demographic Characteristics of Applicants to, and Students of, Ontario Physiotherapy Education Programs, 2004–2014: Trends in Gender, Geographical Location, Aboriginal Identity, and Immigrant Status
Bibliographic record
Abstract
Purpose: The authors analyzed the demographics of potential future physiotherapists to determine whether they were representative of the Canadian population. The specific objectives were to examine selected demographic variables from all applicants to and students in Ontario English-language Master of Physical Therapy programmes in admission cycles 2004–2014, inclusive, and to analyze the results as compared with Canadian population data. Method: Anonymized applicant records (n=14,135) were obtained for admission cycles 2004–2014, inclusive. Variables examined for applicants and students included their gender, geographical location from Canadian and international regions, Aboriginal identity, and immigrant status. A descriptive analysis of counts and proportions was conducted for all variables. Results: The majority of applicants were women (70%), from southern Ontario (73%), and Canadian born (82%). Aboriginal and rural applicants made up small proportions of the applicant pool (1% and 12%, respectively). The number of applicants from British Columbia was proportionally high relative to those from other Canadian provinces. Conclusion: Although Ontario's physiotherapy education programmes remain female dominated, the demographics of applicants and students are otherwise mostly representative of the diverse Canadian population, although very low in the number of Aboriginal peoples. Further research is needed to understand the diversity and composition of the Canadian physiotherapy workforce.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".