MétaCan
Menu
← Back to cohort
Record W3161538699 · doi:10.31234/osf.io/vme6c

Culture and Wisdom

2018· preprint· en· W3161538699 on OpenAlexaff
Franki Y. H. Kung, Igor Grossmann

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSituatedConstruct (python library)HumanityAffordanceStrict constructionismPerspective (graphical)Cultural psychologyExpression (computer science)EpistemologyMeaning (existential)PsychologySociologySocial psychologyCognitive psychologyPhilosophy

Abstract

fetched live from OpenAlex

The concept of wisdom is ancient and deeply embedded in the cultural history of humanity. However, only in the last few decades have psychologists begun to study it scientifically. We review emerging insights into the science of wisdom from a cultural psychological perspective, focusing on (a) cultural similarities and differences in epistemological traditions; (b) lay theories of wisdom (e.g., wisdom-related cognitions, affective processes, and prosociality), and (c) the role of socio-cultural affordances for the expression of wisdom-related characteristics in daily life. Overall, evidence suggests that wisdom is a culturally-situated and malleable construct, with culture playing a central role in shaping wisdom-related behaviors, supporting a constructionist account of wisdom and its development. Understanding of ecological and cultural-historical factors for the meaning and expression of wisdom is essential for the further advancement of psychological wisdom 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 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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.017
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.066
GPT teacher head0.431
Teacher spread0.364 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicAging and Gerontology Research→French-language works237,207→