Demographics of Canadian strength and conditioning coaches
Bibliographic record
Abstract
Canadian strength and conditioning (S&C) coaches demographic characteristics are unknown but are necessary to assess the current state of the field. A sample of 215 Canadian S&C coaches were recruited through the Canadian Strength and Conditioning Association's newsletter, the National Strength and Conditioning Association's (NSCA) Canadian Facebook group, and the principal investigator's professional network. Mean age of the sample was 34.1 years (±8.6) years, 77.7% were male, and 90.7% did not consider themselves to be a visible minority. Participants most commonly reported working in the private sector (34.9%), at a university (19.1%), and with provincial or national sport organizations (19.1%). The most common salary range reported was $40,001–$50,000 and $50,001–$60,000 (Canadian dollars) at 13.5% each. The most common certifications reported by Canadian S&C coaches was the NSCA-Certified Strength and Conditioning Specialist (CSCS) (84.4%). The highest education obtained was reported as Bachelor's (54.9%) and Master's degrees (37.8%), and 83.6% reported having degrees directly related to the field of S&C. The archetype demographics of Canadian S&C coaches presented as mid-thirties, male, non-visible minority, with a Bachelor's degree, and the NSCA–CSCS certification. The definition of these characteristics will inform future Canadian S&C coaches, mentors, and inform future research in this area.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".