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Record W2774759990 · doi:10.1177/1524839917743231

The Utility of Physical Activity Micro-Grants: The ParticipACTION Teen Challenge Program

2017· article· en· W2774759990 on OpenAlexaffabout
Subha Ramanathan, Lauren White, Alicia Luciani, Tanya R. Berry, Sameer Deshpande, Amy E. Latimer‐Cheung, Norm O’Reilly, Ryan E. Rhodes, John C. Spence, Guy Faulkner

Bibliographic record

VenueHealth Promotion Practice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of VictoriaUniversity of LethbridgeUniversity of AlbertaUniversity of TorontoQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsPromotion (chess)BusinessSubsidyPhysical activitySustainabilityResource (disambiguation)Public relationsHealth promotionPolitical scienceMedicinePublic healthNursing

Abstract

fetched live from OpenAlex

Youth physical activity levels remain low in Canada and worldwide. Lack of environmental resources (e.g., access to equipment and facilities, transportation options, and participation costs) is a key barrier for youth participation. Micro-grants are small budgets of money awarded via grant applications and may help community organizations facilitate youth physical activity participation by alleviating environmental resource barriers. ParticipACTION Teen Challenge was a national micro-grant scheme administered in Canada. Secondary analysis of survey data from Provincial and Territorial coordinators, registered community organizers, and successful grant applicants were used to evaluate the process and outcomes of Teen Challenge. Results showed that the financial subsidy of 500CAD was used mainly toward equipment, instruction, and transportation. Coordinators and community organizers indicated high levels of satisfaction and benefits for communities and teens. A key benefit for coordinators was leveraging the Teen Challenge network for physical activity promotion. Reported benefits for teenaged participants included leadership opportunities (e.g., helping create and implement programs) and increased physical activity participation. Findings highlight the value of micro-grants for supporting sport and physical activity opportunities for Canadian teens, and show that such schemes address barriers related to environmental resources. The sustainability of micro-grant schemes remains to be seen.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.976

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.166
GPT teacher head0.497
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations10
Published2017
Admission routes2
Has abstractyes

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