Attractiveness Bias in the Evaluation of Young Pianists' Performances
Bibliographic record
Abstract
We investigated how the attractiveness bias that influences the judgment of a variety of characteristics and behaviors in infants, children, and adults affects the evaluation of young pianists' performances. The assumption was that both the visual and the audio components of a videotaped musical performance influence the viewers perception of performance quality. We asked children, musicians, and nonmusicians (n = 75) to rate the quality of 10 piano performances from audiotapes (sound only) and from videotapes (sound and image). Additionally, the participants rated the attractiveness of the performers from brief videos of the performers getting ready to play. Results show that evaluations of audiovisual recordings of musical performances are judged more reliably than are audio recordings but also suggest that they may be affected by an attractiveness bias. The bias was found to favor the more attractive pianists among the female performers and among the best players, and the less attractive pianists among the male performers. The decision to use more reliable means of evaluation (videotapes or DVDs) at the expense of favoring a particular group of performers would have to be taken carefully depending on the outcomes of the situation.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".