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Ageing, place and voluntarism: towards a geographical perspective on third sector organisations and volunteers in ageing communities

2014· article· en· W2899824209 on OpenAlexafffundabout
Mark W. Skinner

Bibliographic record

VenueVoluntary Sector Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council of CanadaTrent University
KeywordsVoluntarism (philosophy)Transformative learningPerspective (graphical)EmbeddednessAgeingSociologyOlder peopleActive ageingPublic relationsPolitical scienceGerontologySocial scienceMedicine

Abstract

fetched live from OpenAlex

This article addresses the gap within discourses on ageing that call for greater involvement of the third sector in support of older people, but do not account for the difference ‘place’ makes to understanding third sector activities and volunteering. It reviews recent developments in the literature that highlight the importance of place-based approaches, particularly the emergent view of voluntarism as a transformative process that shapes and is shaped by the interactions between older people and their ageing communities. The link between ageing, place and voluntarism is illustrated via a case study of volunteer-based community support for older people in Canada’s most rapidly ageing municipality. Findings from an inventory, survey, focus groups and interviews in Peterborough, Ontario reveal the complexity, interdependence and place-embeddedness behind a successful yet potentially unsustainable response to the challenge of supporting older people. The paradox of relying on under-resourced third sector organisations and older volunteers is highlighted.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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 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

Citations31
Published2014
Admission routes3
Has abstractyes

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