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A Polish adaptation of the Self-Assessed Wisdom Scale (SAWS) in older adults

2022· article· pl· W4284988756 on OpenAlexaff
Paweł Brudek, Katarzyna Cyranka, Jeffrey Dean Webster

Bibliographic record

VenuePsychiatria Polska · 2022
Typearticle
Languagepl
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsLangara College
Fundersnot available
KeywordsTheologyPhysicsPhilosophy

Abstract

fetched live from OpenAlex

OBJECTIVES: The paper presents the results of work on the Polish adaptation of the Self-Assessed Wisdom Scale (SAWS). It presents the psychometric properties of the Polish version of the tool. METHODS: The research was quantitative in nature and it was carried out in a correlation scheme. The respondents completed a set of questionnaires. 880 subjects aged 60-80 years (M = 68.15; SD = 5.96) participated in the study. Apart from the SAWS six other psychological methods were used. The selection of measuring tools was purposeful. RESULTS: The final Polish version of the SAWS consists of 40 items (including 36 diagnostic ones) that make up 5 dimensions of wisdom: (1) "Critical Life Experience", (2) "Emotional Regulation", (3) "Reminiscence and Reflectiveness",(4) "Openness" and (5) "Humor". The reliability index for the entire scale (36 items) was α = 0.92 (very high). Reliability values (Cronbach's α) for individual scales vary from α = 0.60 to α = 0.84. The validity of the scale was evaluated by means of confirmatory analysis. CONCLUSIONS: The results are consistent with the original version of the scale, thus it has been indicated that the Polish version of the SAWS fulfils the psychometric requirements for psychological tests. The scale can be applied in scientific 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
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
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.314
Teacher spread0.297 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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