The role of working memory capacity in evaluative judgments of liking and beauty
Bibliographic record
Abstract
Judgments of liking and beauty appear to be expressions of a common hedonic state, but they differ in how they engage cognitive processes. We hypothesized that beauty judgments place greater demands on limited executive resources than judgments of liking. We tested this hypothesis by asking two groups of participants to judge works of visual art for their beauty or liking while having to remember the location of 1, 3, or 5 dots in a 4 by 4 matrix. We also examined the effect of individual differences in working memory capacity. Our results show that holding information about the location of the dots in working memory delayed judgments of beauty but not of liking. Also, the greater participants’ working memory capacity, the faster they completed the working memory task when judging liking, but not when judging beauty. Our study provides evidence that judging beauty draws more on working memory resources than judging liking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".