A brief history of exercise clearance and prescription: 2.Canadian contributions to the development of objective, evidence-based procedures
Bibliographic record
Abstract
Objective. The aim of this 2-part article is to provide a brief chronicle of the development of exercise clearance and prescription procedures over the past century. Part 1 considered the era when medical interest in exercise was limited, and any advice from physical educators and kinesiologists was based largely upon pulse rate recovery curves. Part 2 considers the development of objective, evidence-based procedures for exercise screening and prescription that began in the 1960s, with a particular emphasis upon the contributions of Canadian exercise scientists. A new interest in fitness and physical activity was sparked by a speech given to the Canadian Medical Association by the Duke of Edinburgh in 1959. This article begins by considering his comments and the reactions of the Federal government. It notes the resulting establishment of 3 Fitness Research Units across Canada, looking specifically at the Toronto Fitness Research Unit and its objectives. The goals of the Toronto unit included not only academic research and the establishment of doctoral and post-doctoral programmes in exercise science, but also many "applied" research tasks: increasing interest of the medical profession in physical activity, preparing for assessments of national fitness, benchmarking existing national levels of fitness, and clarifying the risks of vigorous exercise. These objectives led to the development of a simple and effective exercise screening procedure (the PAR-Q test), and the development of procedures for mass fitness testing (particularly the Canadian Aerobic Fitness Test, CAFT). We conclude this segment of our history by documenting evolution of both the PAR-Q and the Canadian Aerobic Fitness Test to their present objective, evidence-based and computerized format.
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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".