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Record W1985627283 · doi:10.2190/ag.65.2.d

Measuring the Character Strength of Wisdom

2007· article· en· W1985627283 on OpenAlexaff
Jeffrey Dean Webster

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2007
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsLangara College
Fundersnot available
KeywordsGenerativityCronbach's alphaOperationalizationPsychologyConfirmatory factor analysisScale (ratio)Construct validityPsychosocialExploratory factor analysisConstruct (python library)Test (biology)PsychometricsDevelopmental psychologyClinical psychologyStructural equation modelingStatisticsPsychiatryMathematicsCartographyComputer science

Abstract

fetched live from OpenAlex

This study examined the psychosocial correlates and psychometric properties of the Self-Assessed Wisdom Scale (SAWS). Seventy-three men and 98 women ranging in age from 17-92 years (Mean age = 42.77) completed an expanded, 40-item version of the SAWS, the Loyola Generativity Scale, and the Experiences in Close Relationships Scale. A new definition of wisdom is provided which is operationalized with the SAWS. Results indicated that the SAWS has excellent reliability (test-retest = .838; Cronbach's Alpha = .904). Exploratory and Confirmatory Factor analyses confirmed the five hypothesized dimensions of wisdom and the total SAWS score correlated in predicted directions with generativity (r(169) = .448; p < .01) and attachment avoidance (r(169) = -.239, p < .01) demonstrating construct validity.

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)0.001
metaresearch head score (Gemma)0.012
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.367
Teacher spread0.294 · 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

Citations286
Published2007
Admission routes1
Has abstractyes

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Same venueThe International Journal of Aging and Human DevelopmentSame topicAging and Gerontology ResearchFrench-language works237,207