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Record W2690138357

How Creativity and the Arts Enhanced the Life of a Chinese Elderly Immigrant in Canada: A Shared Exploration of a Life Lived Fully

2011· dissertation· en· W2690138357 on OpenAlexaboutno aff
Kit Yin Au

Bibliographic record

VenueNational University System Repository (National University System) · 2011
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityThe artsImmigrationLived experienceVisual artsSociologyPsychologyAestheticsGerontologyHistoryArtSocial psychologyPsychoanalysisMedicine
DOInot available

Abstract

fetched live from OpenAlex

How do creativity and the arts have positive influence on the aging process of a Chinese elderly immigrant in Canada? Fisher and Specht (as cited in Reynolds, 2010) suggested that visual art making in later life contributes to the older adults’ well-being in several ways, such as gaining a sense of achievement, purpose in life, and connection with others. In this thesis, I describe my conversations with a 94-year old Chinese senior who is fully engaged in the arts and creative activities, and explore her perception of the positive effects that arts have on her as she ages. Research on aging has indicated that older people who are engaged in activities that provide them with a sense of mastery have more positive health outcomes (as cited in Cohen, 2006). Feeling a sense of mastery in an area results in a sense of control of one’s self, which leads to an increased feelings of empowerment. Art activities help to keep the elders’ minds challenged thus make their brains healthier (Cohen, 2006). Art-making process allows older adults to express emotions, which in turn can be healing, satisfying, and meaningful (Rugh, 1991). Older people are vulnerable to social isolation and restrictions in doing activities, particularly those who are in poor health. Engaging in the arts helps them to maintain their value as a person in the world and to stay closely connected to the rest of the world, instead of being stereotyped by age or disability (Reynolds, 2010).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.414
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.210
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; a candidate call from one teacher head, 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
Published2011
Admission routes1
Has abstractyes

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