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Record W2601287376 · doi:10.1177/1745691616672066

Wisdom in Context

2017· review· en· W2601287376 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerspectives on Psychological Science · 2017
Typereview
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHumilityExperiential learningPsychologySituational ethicsContext (archaeology)EpistemologySet (abstract data type)Critical thinkingCognitionSocial psychologyCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

Philosophers and psychological scientists have converged on the idea that wisdom involves certain aspects of thinking (e.g., intellectual humility, recognition of uncertainty and change), enabling application of knowledge to life challenges. Empirical evidence indicates that people's ability to think wisely varies dramatically across experiential contexts that they encounter over the life span. Moreover, wise thinking varies from one situation to another, with self-focused contexts inhibiting wise thinking. Experiments can show ways to buffer thinking against bias in cases in which self-interests are unavoidable. Specifically, an ego-decentering cognitive mind-set enables wise thinking about personally meaningful issues. It appears that experiential, situational, and cultural factors are even more powerful in shaping wisdom than previously imagined. Focus on such contextual factors sheds new light on the processes underlying wise thought and its development, helps to integrate different approaches to studying wisdom, and has implications for measurement and development of wisdom-enhancing interventions.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.004

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 head0.375
GPT teacher head0.606
Teacher spread0.231 · 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