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Record W2890158716 · doi:10.1017/s0144686x18001150

Enacting agency: exploring how older adults shape their neighbourhoods

2018· article· en· W2890158716 on OpenAlexaff
Carri Hand, Debbie Laliberté Rudman, Suzanne Huot, Rachael Pack, Jason Gilliland

Bibliographic record

VenueAgeing and Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsSocial connectednessNeighbourhood (mathematics)CasualSociologyAgency (philosophy)Citizen journalismSense of agencyEthnographySense of communityCollective actionSocial psychologyPublic relationsPsychologyPolitical sciencePoliticsSocial science

Abstract

fetched live from OpenAlex

Abstract Within research on ageing in neighbourhoods, older adults are often positioned as impacted by neighbourhood features; their impact on neighbourhoods is less often considered. Drawing on a study exploring how person and place transact to shape older adults’ social connectedness, inclusion and engagement in neighbourhoods, this paper explores how older adults take action in efforts to create neighbourhoods that meet individual and collective needs and wants. We drew on ethnographic and community-based participatory approaches and employed qualitative and geospatial methods with 14 older adults in two neighbourhoods. Analysis identified three themes that described the ways that older adults enact agency at the neighbourhood level: being present and inviting casual social interaction , helping others and taking community action . The participants appeared to contribute to a collective sense of connectedness and creation of social spaces doing everyday neighbourhood activities and interacting with others. Shared territories in which others were present seemed to support such interactions. Participants also helped others in a variety of ways, often relating to gaps in services and support, becoming neighbourhood-based supports for other seniors. Finally, participants contributed to change at the community level, such as engaging politically, patronising local businesses and making improvements in public places. Study findings suggest the potential benefits of collaborating with older adults to create and maintain liveable neighbourhoods.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.305
Teacher spread0.253 · 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 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

Citations44
Published2018
Admission routes1
Has abstractyes

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