Artistic-Value Descriptions Are Associated with Higher Aesthetic Ratings than Social-Value Descriptions for AI-Generated Variants of Classical Paintings
Aug 2026· Behavioral Science· Vol 16, pp. 1437· 0 citations· 31 references
Medicine
Abstract
Contextual meaning can influence art evaluation even when viewers encounter images within a structured visual stimulus family. This exploratory questionnaire-version study examined whether value-oriented textual descriptions were associated with aesthetic ratings of AI-generated variants of classical paintings in three Chinese-language questionnaire versions emphasising cultural value, artistic value, or social value. The available dataset contained 61 participants, each rating 40 images on a 1–10 aesthetic scale, yielding 2440 complete observations. A post hoc three-rater manipulation check of 30 image–description pairs found that all evaluated pairs satisfied the applied validation criterion; inter-rater reliability across item–dimension judgments was high at ICC(2,k) = 0.936. The primary analysis used a linear mixed-effects model with crossed random intercepts for participant and stimulus identity, and a fuller by-stimulus random-slope model was estimated as a diagnostic response to review. Relative to social-value descriptions, artistic-value descriptions were associated with higher ratings in the random-intercept model, where b = 1.74, SE = 0.57, z = 3.03, p = 0.002, 95% CI [0.62, 2.87], and this contrast also persisted in the diagnostic by-stimulus random-slope model, although that model converged with a non-positive-definite Hessian. Cultural-value descriptions were intermediate and should not be interpreted as showing a stable general advantage over social-value descriptions. The results therefore provide qualified evidence for an artistic-versus-social framing association, not a confirmed causal effect of all value-cue conditions. Interpretation remains bounded by the modest sample, undocumented allocation procedure, rapid-completion records, incomplete prompt metadata, and post hoc validation of a representative rather than exhaustive stimulus set.
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