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Record W2993389699 · doi:10.3390/ijerph16244916

Perspectives on Active Transportation in a Mid-Sized Age-Friendly City: “You Stay Home”

2019· article· en· W2993389699 on OpenAlexafffundabout
Irmina Klicnik, Shilpa Dogra

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsOntario Tech University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSocioeconomic statusNoveltyFocus groupActive livingGerontologyCommunity designPsychologyBusinessGeographyEnvironmental healthMarketingPublic healthMedicinePopulationPolitical scienceSocial psychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Active transportation is an affordable and accessible form of transportation that facilitates the mobility of older adults in their communities. Age-friendly cities encourage and support physical activity and social participation among older adults; however, they often do not adequately address active transportation. Our goal was to identify and understand the constraints to active transportation that older adults experience in order to inform the development of viable solutions. METHODS: Focus group interviews were conducted with community dwelling older adults (n = 52) living in the City of Oshawa in Ontario, Canada; each focus group targeted a specific demographic to ensure a diverse range of perspectives were represented. Data were analyzed to identify themes; sub-group analyses were conducted to understand the experience of those from low socioeconomic status and culturally diverse groups. RESULTS: Themes pertaining to environmental, individual, and task constraints, as well as their interactions, were identified. Of particular novelty, seemingly non-modifiable constraints (e.g., weather and personal health) interacted with modifiable constraints (e.g., urban design). Culturally diverse and lower socioeconomic groups had more favorable perspectives of their neighborhoods. CONCLUSION: While constraints to active transportation interact to exacerbate one another, there is an opportunity to minimize or remove constraints by implementing age-friendly policies and practices.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.086
GPT teacher head0.458
Teacher spread0.372 · 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 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

Citations38
Published2019
Admission routes3
Has abstractyes

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