MétaCan
Menu
Back to cohort
Record W2127644454 · doi:10.1017/s0714980813000408

Age-Friendly Rural Communities: Conceptualizing ‘Best-Fit’

2013· article· fr· W2127644454 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsDiversity (politics)Context (archaeology)Rural communitySociologyAging in placePublic relationsPsychologyGeographyPolitical scienceGerontologySocioeconomicsMedicine

Abstract

fetched live from OpenAlex

The literature on age-friendly communities is predominantly focused on a model of urban aging, thereby failing to reflect the diversity of rural communities. In this article, we address that gap by focusing on the concept of community in a rural context and asking what makes a good fi t between older people and their environment. We do this through (a) autobiographical and biographical accounts of two very different geographical living environments: bucolic and bypassed communities; and through (b) analysis of the different needs and resources of two groups of people: marginalized and community-active older adults, who live in those two different rural communities. We argue that the original 2007 Health Organization definition of age friendly should be reconceptualized to explicitly accommodate different community needs and resources, to be more inclusive as well as more interactive and dynamic, incorporating changes that have occurred over time in people and place.

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.024
GPT teacher head0.249
Teacher spread0.226 · 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