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Record W2171827897 · doi:10.21225/d5mw2d

Older Adults’ Participation in Education and Successful Aging: Implications for University Continuing Education in Canada

2010· article· en· W2171827897 on OpenAlexvenueaboutno aff
Atlanta Sloane-Seale, Bill Kops

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2010
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologyLifelong learningSuccessful agingPopulation ageingPsychologyPerceptionPopulationSpiritualitySociologyMedicinePedagogyDemographyAlternative medicine

Abstract

fetched live from OpenAlex

Representatives from Manitoba seniors’ organizations and the University of Manitoba collaborated on a proposal to examine the participation of older adults in learning activities. The initiative led to a series of studies on this theme, including an exploration of participation at a seniors’ centre (Sloane-Seale & Kops, 2004), a comparison of participants and non-participants at three selected urban seniors’ centres (Sloane-Seale & Kops, 2007), and an analysis of participation at several urban and rural seniors’ centres, as well as participants’ perceptions of the characteristics of successful aging (Sloane-Seale & Kops, 2008). Building on these previous studies, the study described in this article examined the participation of older adults in Manitoba and how it links to successful aging. Key statistics relating to older adults’ participation, types of educational activities, learning in later life, and characteristics of successful aging were collected. The results suggest that such participation leads to a more inclusive and comprehensive understanding of successful aging; that educational activities positively influence mental and physical activity, which in turn result in more positive health and well- being; and that spirituality and life planning, including a positive sense of self, a focus on personal renewal and growth, a connection to the broader community, and setting life goals, contribute to successful aging. In light of Canada’s aging population, these findings have implications for educational gerontology, lifelong learning, and continuing education practice and research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.295
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations26
Published2010
Admission routes2
Has abstractyes

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