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Record W2131668478 · doi:10.14288/hfjc.v2i1.24

Careers Opportunities for Exercise Science/Kinesiology Graduates

2010· article· en· W2131668478 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Collections · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAthletic Training and Education
Canadian institutionsYork University
Fundersnot available
KeywordsKinesiologyTrainerMedical educationBiopsychosocial modelSports sciencePsychologyPromotion (chess)Physical therapyMedicineAlternative medicineNursingPolitical science

Abstract

fetched live from OpenAlex

Exercise Science / Kinesiology is the study of physiological and functional adaptations to movement. Career opportunities for individuals who graduate with degrees in Exercise Science / Kinesiology are numerous. Some of the most common examples are: Personal Trainer, Strength and Conditioning Coach, Exercise Physiologist, Employee Fitness Director, Cardiopulmonary Rehabilitation Specialist, Biomechanist / Ergonomist, Athletic Trainer, Community College Professor, University Professor / Researcher, Municipal, Provincial & Federal Health Promotion Administrator, Pharmaceutical Drug Trial Manager and Research Co-ordinator for Chronic Disease Granting Agencies. Some common related careers requiring additional training are: Dietician / Sports Nutritionist, Physiotherapist / Physical Therapist, Medical Doctor, Chiropractor, Respiratory Therapist, Massage Therapist and Nurse / Nurse Practitioner.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.251
GPT teacher head0.462
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it