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Record W2764054897 · doi:10.1177/0956797617722621

The Wisdom in Virtue: Pursuit of Virtue Predicts Wise Reasoning About Personal Conflicts

2017· article· en· W2764054897 on OpenAlexafffund
Alex C. Huynh, Harrison Oakes, Garrett R. Shay, Ian McGregor

Bibliographic record

VenuePsychological Science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsVirtueHumilityPsychologyPerspective (graphical)Social psychologyConstruct (python library)Goal pursuitEpistemologyLaw

Abstract

fetched live from OpenAlex

Most people can reason relatively wisely about others' social conflicts, but often struggle to do so about their own (i.e., Solomon's paradox). We suggest that true wisdom should involve the ability to reason wisely about both others' and one's own social conflicts, and we investigated the pursuit of virtue as a construct that predicts this broader capacity for wisdom. Results across two studies support prior findings regarding Solomon's paradox: Participants ( N = 623) more strongly endorsed wise-reasoning strategies (e.g., intellectual humility, adopting an outsider's perspective) for resolving other people's social conflicts than for resolving their own. The pursuit of virtue (e.g., pursuing personal ideals and contributing to other people) moderated this effect of conflict type. In both studies, greater endorsement of the pursuit of virtue was associated with greater endorsement of wise-reasoning strategies for one's own personal conflicts; as a result, participants who highly endorsed the pursuit of virtue endorsed wise-reasoning strategies at similar levels for resolving their own social conflicts and resolving other people's social conflicts. Implications of these results and underlying mechanisms are explored and discussed.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0030.000
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 head0.113
GPT teacher head0.361
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

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

Citations50
Published2017
Admission routes2
Has abstractyes

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