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Record W2726498187 · doi:10.1093/geroni/igx004.3873

DOES RELIGIOUS EXPERIENCE, SPIRITUALITY, AND QUALITY OF LIFE PREDICT WISDOM? A CROSS-AGE ANALYSIS

2017· article· en· W2726498187 on OpenAlexaff
Hyeyoung Bang, Michel Ferrari

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReligiositySpiritualityBivariate analysisPsychologyQuality of life (healthcare)DemographyGerontologySocial psychologyMedicineSociologyAlternative medicine

Abstract

fetched live from OpenAlex

Our on-going mixed-methods study examines the relationship between wisdom and other variables such as religiosity, spirituality, and quality of life among 75 Canadians and 89 South Koreans (total 164) in two age groups: 106 younger adults [age 18–25], and 58 older adults [age 60–85]). Multiple regression and bivariate correlation analyses reveal that these variables predict wisdom in both age groups, although quality of life is the only significant variable to predict wisdom in both groups. Only quality of life is correlated to the total wisdom score in the younger groups, whereas quality of life, religious experience, and spirituality are positively related to wisdom in the older age groups. Interestingly though, the elders’ daily spiritual experience is negatively related to wisdom. The results show that elders in both countries who seek spirituality, religious experience and belief are more likely wise, and their wisdom may link to their quality of life.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.443
Teacher spread0.365 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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