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Record W2146861510 · doi:10.1123/jpah.2012-0178

Designing Active Communities: A Coordinated Action Framework for Planners and Public Health Professionals

2014· article· en· W2146861510 on OpenAlexafffundabout
Kim Bergeron, Lucie Lévesque

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsAction (physics)Public healthPublic relationsPsychologyMedicinePolitical scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Community design can have a positive or negative influence on the physical activity level of residents. The complementary expertise of professionals from both planning and public health is needed to build active communities. The current study aimed to develop a coordinated framework for planners and public health professionals to enhance the design of active communities. METHODS: Planners and public health professionals working in Ontario, Canada were recruited to participate in a concept mapping process to identify ways they should work together to enhance the design of active communities. RESULTS: This process generated 72 actions that represent collaborative efforts planners and public health professionals should engage in when designing active communities. These actions were then organized by importance and feasibility. This resulted in a coordinated action framework that includes 19 proximal and 6 distal coordinated actions for planners and public health professionals. CONCLUSION: Implementation of the recommended actions has the potential to make a difference in community design as a way to enhance physical activity in community members. This Coordinated Action Framework provides a way to address physical inactivity from an environmental and policy standpoint.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.279
GPT teacher head0.516
Teacher spread0.237 · 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 designOther design
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

Citations15
Published2014
Admission routes3
Has abstractyes

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