Singers take center stage! Personality traits and stereotypes of popular musicians
Bibliographic record
Abstract
Despite some evidence that performing musicians tend to have distinct personality characteristics, there is little understanding of how specific positions in bands might be correlated with certain traits. Moreover, there is the possibility that such correlations are exaggerated via stereotypic social perception. In an online sample of popular musicians (including 87 bassists, 48 drummers, 115 guitarists, and 30 vocalists), we evaluated (a) differences in self-reported personality characteristics along the Big Five dimensions; and (b) perceptions of each kind of musician in terms of social category membership (e.g., “What are guitar players like?”). Singers were significantly more extraverted than bassists, and more open to experience than drummers. Whereas there were few differences among other musicians in self-reported personality, the various categories evinced stereotypes that were moderated by participants’ own positions in the band. For example, bass players were generally seen as the most agreeable band members, but this was especially true in the eyes of the bassists themselves. Results are interpreted with reference to biases associated with social categorization and group membership.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".