Sad Art Gives Voice to Our Own Sadness
Bibliographic record
Abstract
People tend to show greater liking for expressions of sadness when these expressions are described as art. Why does this effect arise? One obvious hypothesis would be that describing something as art makes people more likely to regard it as fictional, and people prefer expressions of sadness that are not real. We contrast this obvious hypothesis with a hypothesis derived from the philosophical literature. In this alternative hypothesis, describing something as art makes people more inclined to appropriate it, that is, to see it as an expression of their own sadness. Study 1 found that describing the exact same sad text as art (e.g., a monologue) as opposed to not-art (e.g., a diary entry) led to increased liking for the work. Study 2 showed that this effect is not mediated by fictionality. Study 3 showed that the effect is mediated by appropriation. Study 4 looked at the impact of a manipulation of fictionality. Describing a work as fictional did lead to increased liking, but this effect was completely mediated by appropriation. These results provide at least some initial support for the appropriation hypothesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".