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Record W4404767843 · doi:10.1017/s0714980824000369

Neighbourhood Walkability and Greenness Exhibit Different Associations with Social Participation in Older Males and Females: An Analysis of the CLSA

2024· article· en· W4404767843 on OpenAlexafffundabout
Irmina Klicnik, Andrew Putman, David Rudoler, Michael J. Widener, Shilpa Dogra

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of TorontoOntario Tech University
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsLonelinessWalkabilityNeighbourhood (mathematics)GerontologyPsychologyDemographyLongitudinal studyCohortSocial engagementMedicineBuilt environmentEcologySocial psychologySociologyBiology

Abstract

fetched live from OpenAlex

We explored the relationship between neighbourhood and social participation among older adults using a Living Environments and Active Aging Framework. This prospective cohort study used baseline data from the Canadian Longitudinal Study on Aging (CLSA) with a 3-year follow-up. Three aspects of social participation were the outcomes; walkability and greenness at baseline were exposure variables. The sample consisted of 50.0% females (n=16,735, age 72.9± 5.6 years). In males, higher greenness was associated with lower loneliness and less variety in social activities. No significant associations between greenness and social participation were found in females. High walkability was related to a higher variety of social activity and higher loneliness in males but not females, and less desire for more social activity in both sexes. Greenness and walkability impact social participation among older adults. Future research should include sex and gender-based analyses.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicUrban Green Space and HealthFrench-language works237,207