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Record W2900265254 · doi:10.1093/geroni/igy023.3098

VOICES OF OLDER ADULTS IN AGING IN PLACE RESEARCH: LEARNINGS FROM PHOTOVOICE METHOD

2018· article· en· W2900265254 on OpenAlexaffabout
Catherine Bigonnesse, Habib Chaudhury

Bibliographic record

VenueInnovation in Aging · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSimon Fraser UniversityUniversité de Moncton
Fundersnot available
KeywordsPhotovoiceNeighbourhood (mathematics)Aging in placePresentation (obstetrics)Constructivist grounded theoryPsychologyGerontologySociologyGrounded theoryQualitative researchMedicineSocial scienceVisual arts

Abstract

fetched live from OpenAlex

This presentation reports findings of a multi-case study of the influence of the social and physical environments of home and neighbourhood on the processes of aging in place. Twenty older adults living in three Cohousing and two Naturally Occurring Retirement Communities (NORC) in British Columbia, Canada were recruited to conduct photovoices and semi-structured interviews. Data was collected and analyzed adopting the constructivist grounded theory methodology. Focusing on methodological aspects of conducting photovoice with older adults, an overview of the photovoice process is first provided. Lessons learned related to ethics, participants’ characteristics, technology literacy and analysis strategies will be discussed. Photovoice proved to be a suitable tool to document complex processes of aging in place and a powerful method to capture older adults’ subjective experiences of their home and neighbourhood. The method provided them an opportunity to meaningfully engage in the topic and communicate their unique perspectives with insightful visual representations.

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)0.034
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.009
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.513
GPT teacher head0.646
Teacher spread0.133 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes2
Has abstractyes

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