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Record W2729942296

Impacts of a new Greenway on older adult mobility: A mixed-methods analysis in Vancouver, BC

2017· dissertation· en· W2729942296 on OpenAlexfundaboutno aff
Caitlin Mary Pugh

Bibliographic record

VenueSummit (Simon Fraser University) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchSimon Fraser UniversityMichael Smith Health Research BC
KeywordsGeographyGerontologyRegional scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Our population is aging, and life expectancies are increasing globally. One strategy to promote healthy aging is by creating environments that support physical activity. Using a natural experiment study design, this dissertation takes a mixed-methods approach to capture the impacts of a built environment intervention aimed to increase active transportation among community-dwelling older adults. We captured location-specific travel and physical activity using accelerometers and GPS monitors one year before and after the Comox-Helmcken Greenway was developed, and measured change in weekly transportation-related activity, specific activity along the Greenway, and activity along a comparison corridor. Secondly, we interviewed a subset of these older adults to capture their perceptions of the Greenway. We found no change in weekly physical activity levels, but a decrease in the number of trips along the Greenway. Our interview data suggests this may result from confusion of messaging, the steep slope, and a lack of destinations.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0030.000
Open science0.0010.002
Research integrity0.0010.001
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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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 designQualitative
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

Citations0
Published2017
Admission routes2
Has abstractyes

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