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Record W2923731398 · doi:10.1177/0091415019836098

Effects of Causal Attribution and Implicit Mind-Set on Wisdom Development

2019· article· en· W2923731398 on OpenAlexaffabout
Fatemeh Alhosseini, Michel Ferrari

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2019
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAttributionSet (abstract data type)PsychologyDevelopment (topology)EpistemologyCognitive psychologyCognitive scienceComputer scienceSocial psychologyPhilosophyMathematics

Abstract

fetched live from OpenAlex

This study investigates the relationship between motivation and the development of wisdom. Eighty Canadian participants were interviewed and completed Ardelt's Three-Dimensional Wisdom Scale (3D-WS). Using a mixed method design, we assessed wisdom definitions, interpersonal causal attributions, and mind-set about developing wisdom. A chi-square analysis revealed a significant relationship between attribution and mind-set about wisdom development. Two multivariate analyses of variance showed that both factors significantly influenced wisdom scores on the 3D-WS. These results suggest that people who consider wisdom development to be controllable and believe that their personal wisdom can be developed (i.e., growth mind-set) tend to be wiser, regardless of their definition of wisdom. By introducing the importance of mind-set and attribution, this study will open new avenues for research on teaching for wisdom and allow educators to develop programs to cultivate wisdom that focus on altering attribution and mind-set.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.360
Teacher spread0.327 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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