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Record W2987015904 · doi:10.1093/geroni/igz038.062

CRITICAL PERSPECTIVES ON VOLUNTARISM IN AGING RURAL COMMUNITIES: VOLUNTEER LEADERSHIP BIOGRAPHIES

2019· article· en· W2987015904 on OpenAlexaffabout
Mark W. Skinner, Alun E. Joseph

Bibliographic record

VenueInnovation in Aging · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of GuelphTrent University
Fundersnot available
KeywordsVoluntarism (philosophy)Transformative learningQualitative researchEconomic growthPublic relationsSociologyResource (disambiguation)Political scienceSocial sciencePedagogy

Abstract

fetched live from OpenAlex

Abstract Voluntarism has been portrayed as a productive and even transformative process whereby rural communities, households and older residents are able to meet the challenges of changing rural demographics. Yet, little attention has been paid to building a critical perspective on the complex and often-contested expectations placed on older rural volunteers. This paper focuses on the particular gap in understanding the contributions of older rural adults as a crucial resource in creating opportunities for aging in place and sustainable rural community development. Drawing on research into voluntarism in Canada’s aging resource communities, this paper presents qualitative findings from innovative ‘volunteer leadership biographies’ with older residents who were involved in key voluntary sector initiatives to improve community development. The findings show how older volunteer leadership is embedded in both place (residency) and time (life course), revealing new dimensions to the problem of understanding volunteer leadership in an era of rural population change.

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)0.011
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.022
Scholarly communication0.0060.004
Open science0.0010.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.321
Teacher spread0.275 · 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 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

Citations0
Published2019
Admission routes2
Has abstractyes

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