Bibliographic record
Abstract
The evolution of sports science has seen the emergence of different forms of employment: practicing sports scientists in state-sponsored (primarily) Olympic sports, academic researchers with an interest in sports physiology and sports performance, self-employed private practitioners, and team-based support staff with a blend of coaching, sports science, and strength and conditioning duties.Like most jobs, the key issues are the type and interest of the work, level of remuneration, job security, and future growth prospects for the individual and discipline.The position of practicing sports scientists continues to emerge in selected sports.Many nations and their national sporting programs employ or contract sports scientists in the quest for international success.Historically, much of this work has been conducted in the individual sports, such as cycling, rowing, swimming, triathlon, and distance running, where physiological characteristics and capacities are important determinants of performance.The United States has a unique sports system, with only a limited number of sports scientists working directly with summer and winter Olympic sports.This is offset by a huge collegiate and professional sports system that offers unparalleled resources and opportunities for researchers, students, and practitioners.The challenge for other nations is to build sports science into their sporting system as a fundamental element.At times, sports science and sports physiology are considered luxuries and lower in the list of priorities than (essential) disciplines, such as strength and conditioning, sports medicine, and physical therapies.Some countries, such as Russia, Germany, and Canada, that were leaders in the emergence of sports science in the 1960's, 70's, and 80's have faced significant challenges as the field has matured internationally.Can countries like China, Japan, and India capitalize on their emerging economic strength and sporting prowess to take sports physiology and performance enhancement to another level?Academic research is another active of area of exercise and sports science research.The balance between these two subdisciplines has changed substantially in the last 5 years with a worldwide focus on physical activity, obesity, metabolic syndrome, and related lifestyle and medical issues.The funding for these biomedical areas is often orders of magnitude greater than that directed to sports physiology and performance.Only a few years ago, most postgraduate projects were focused on sports science and exercise/sports performance.Nowadays, most graduate student projects are in the area of physical activity.This trend has also changed the face of undergraduate programs.The previous emphasis of courses in exercise physiology and sport performance is being replaced by physical activity for special populations, exercise programs for the sedentary or obese, and other lifestyle issues.Universities are recruiting staff with expertise and skills in these areas, and, of course, with matching publication and funding track records.Internal university and department funding is directed toward physical activity, so those staff members and students
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.040 | 0.009 |
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".