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Record W2885923414 · doi:10.1093/heapro/day063

University-based physical literacy programming for children: Canadian community stakeholders’ recommendations

2018· article· en· W2885923414 on OpenAlexaffabout
Kyoung June Yi, Erin Cameron, Matthew Patey, Angela Loucks‐Atkinson, TA Loeffler, Erin McGowan, Anne‐Marie Sullivan, Christopher Borduas, Richard Buote

Bibliographic record

VenueHealth Promotion International · 2018
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMemorial University of NewfoundlandNOSM UniversityLakehead UniversityUniversity of Manitoba
Fundersnot available
KeywordsLiteracyHealth literacyPolitical sciencePublic relationsPsychologySociologyPedagogy

Abstract

fetched live from OpenAlex

'Physical literacy' (PL) education-that is, teaching foundational skills, attitudes, behaviors and knowledge about lifelong involvements in physical activities, is an important aspect for health promotion among children. Universities have been playing a critical role by teaching future PL professionals. Additionally, various universities have offered university-based PL programming for neighborhood children as a way of public health promotion service and community engagement. However, this additional role of universities and the ways of promoting the quality of this type of health promotion service programming have not been investigated in the current research literature. Therefore, the purpose of this study was to identify the practicable strategies to enhance the quality of university-based PL programming for children from the perspectives of community stakeholders. Overall, 24 community stakeholders who held professional positions that are related to PL education participated in a 90-min focus group interview. This grounded theory study identified that university-based PL programming for children should be (i) inclusive, (ii) collaborative, (iii) welcoming and (iv) responsive. Practical suggestions and recommendations were also provided. This study has provided empirical knowledge to prioritize aspects for the future actions in planning and implementing university-based PL programming for children and informed for further cross-cultural comparisons amongst the perspectives of participants, university service providers and community stakeholders. The knowledge acquired from this research will also be translated to university service providers who operate similar type of health promotion service programming to the public.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.101
GPT teacher head0.380
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2018
Admission routes2
Has abstractyes

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