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Record W1520305922 · doi:10.1111/cag.12087

Growing old in resource communities: Exploring the links among voluntarism, aging, and community development

2014· article· en· W1520305922 on OpenAlexafffundvenueabout
Mark W. Skinner, Alun E. Joseph, Neil Hanlon, Greg Halseth, Laura Ryser

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of Northern British ColumbiaUniversity of GuelphTrent University
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsVoluntarism (philosophy)Resource (disambiguation)Transformative learningPolitical scienceEconomic growthCommunity developmentSociologyEconomics

Abstract

fetched live from OpenAlex

Abstract This article addresses the implications of “resource frontier aging” with a particular emphasis on understanding the role of the voluntary sector in supporting older people living in resource hinterland regions, and in sustaining economic and social development in their communities. Informed by recent calls for greater attention to the diverse experiences of rural aging, individually and collectively, and drawing on previous research on voluntarism in aging rural communities and on community development in Canada's resource hinterland, we conceptualize voluntarism as a multifaceted process that both shapes and is shaped by the interactions between older people and aging places. We articulate an approach for interrogating initiatives that link voluntarism, aging, and community development together, and present findings from an exploratory analysis of local media from two resource towns in northern British Columbia to identify and describe the interrelationship between voluntary sector activities in support of community development and those in support of aging in place. The findings provide evidence of the multiple, nuanced, and reciprocal ways in which voluntarism creates and reinforces the connections between aging and community development, often via the leadership and participation of older residents. Avenues for further research aimed at developing an in‐depth understanding of voluntarism as a potentially transformative process in resource frontier communities are discussed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.003
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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

Citations21
Published2014
Admission routes4
Has abstractyes

Explore more

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