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Record W2617823223

Running: How is it Taught and Evaluated in British Columbia Schools?

2018· article· en· W2617823223 on OpenAlexaffvenueabout
Clare Louise Protheroe, Astrid M. De Souza, Kevin C. Harris, Victoria E. Claydon, Shubhayan Sanatani

Bibliographic record

VenueUBC Faculty of Medicine medical journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsInternational Collaboration On Repair DiscoveriesSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsCurriculumGrading (engineering)Medical educationMedicinePopulationPsychologyPedagogyEngineeringEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Objective Running is a simple and inexpensive exercise to maintain cardiovascular health. We aimed to evaluate the incorporation of running within the curriculum in British Columbian schools to determine whether students are effectively taught how to run to maintain an active lifestyle.Methods All 60 superintendents representing the school districts in British Columbia were contacted. They gave written approval for our research team to send a survey to schools within their districts. Teacher and student perspectives on running in middle and high schools were collected.Results Teachers (n=63) and students (n=597) would like more information on proper running form and the cardiovascular benefits associated with this exercise. There is inconsistency in reporting medical conditions, and it is not clear how grading is distributed fairly among all students (p<0.05).Conclusion There is a lack of education in schools on running. Improvements to the incorporation of running within the physical and health education curriculum may enhance student enjoyment and in turn help reduce sedentary behaviours and associated comorbidities in the general population.

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.326
Teacher spread0.296 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes3
Has abstractyes

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