A content-analysis of job advertisements for exercise professionals in Canada: a need for clarification of qualifications
Bibliographic record
Abstract
Despite the general population seeking out exercise professionals and the strong interest of other healthcare providers in referring patients to exercise professionals, what characterizes an “exercise professional” is poorly understood. The purpose of this study was to summarize the required qualifications and certifications described in job advertisements hiring an “Exercise Professional” in Canada. A common career finding website (Indeed) and other relevant organizations were searched for job advertisements. The specific search terms were “Kinesiology”, “Kinesiologist”, “Exercise Professional”, and “Exercise Physiologist”. Job advertisements that were hiring an exercise professional and described some exercise related duties were included for content analysis. n = 177/1364 unique job advertisements met inclusion criteria. Job titles were grouped into six main categories: Kinesiologist ( n = 88/177), Personal Trainer ( n = 49/177), Fitness Coach/Instructor ( n = 38/177), Strength and Conditioning Specialist ( n = 5/177), Exercise Physiologist ( n = 4/177), and other ( n = 31/177). Most positions required ( n = 101) or preferred ( n = 36) a Kinesiology degree, while n = 48/92 (88 Kinesiology and 4 Exercise Physiologist positions) indicated a need/interest in applicants having a membership with a provincial Kinesiology association/affiliation, n = 8/92 a Clinical Exercise Physiologist certification, and n = 6/92 a general “Kinesiology certification”. This emphasizes the need for unique requirements of exercise professional positions and guidelines for the (di)similar scope of practice across exercise professional training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".