Developing an Intentionally Designed Physical Activity Model of Programming for Children’s Structured Recreation in Canada
Bibliographic record
Abstract
Sport and education organizations have established models to ensure that coaches and teachers understand the physical, social, emotional and mental development of children. Such pathways of intentionally designed models fail to exist in the recreation sector where many physical activity (PA) programs are mainly developed based on convenience and instructor availability rather than on established credentials and current pedagogy practices. Addressing this gap, this paper explores the creation of an intentionally designed model of programming for children’s structured recreation, which is defined as sport or PA-based programs that are planned and led by an instructor. This proposed model is contextualized within the province of Alberta, but may be applicable across the nation. The authors further define “intentionally designed” as the development of purposeful programming with specific objectives that align with outside sources. One such source comes from the Canadian Parks and Recreation Association, who has created a Canadian Recreation Framework, an initiative to ultimately develop the well-being of all Canadians. The proposed, structured recreation model also incorporates several guiding principles including physical literacy and sport philosophy. Physical Literacy (PL) focuses on the lived body as the embodied dimension of our human experience, and how it can be enriched through various experiences that enable us to reach our full potential (Whitehead, 2007). It is about viewing the body holistically rather than separate from the entire being. By planning diverse PA in four environments, including land, water, air, and ice, the model also aligns with the sports sector and its philosophy of developing both fundamental movement skills and fundamental sport skills. Moreover, with allocated playing time, intentionally designed structured lesson plans, and one consistent leader in each activity, the model aims to increase the participants’ motor proficiency and levels of PA while building their confidence and competence across distinct exercises. The execution of the proposed recreation model involves a four-month program where participants rotate to a different PA environment each month and attend two classes per week, cumulating in 32 total classes. Management implications are discussed to determine how recreational professionals can achieve the intended outcomes of the model. Finally, further research is necessary to determine if this model can increase participants’ motor proficiency and positively influence physical activity behaviors in the recreation sector.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".