Establishing an empirical profile of self-defined “tone deafness”: Perception, singing performance and self-assessment
Bibliographic record
Abstract
Research has suggested that around 17% of Western adults self-define as “tone deaf” (Cuddy, Balkwill, Peretz & Holden, 2005). But questions remain about the exact nature of tone deafness. One candidate for a formal definition is “congenital amusia” (Peretz et al., 2003), characterised by a dense music-specific perceptual deficit. However, most people self-defining as tone deaf are not congenially amusic (Cuddy et al., 2005). According to Sloboda, Wise and Peretz (2005), the general population defines tone deafness as perceived poor singing ability, suggesting the need to extend investigations to production abilities and self-perceptions. The present research aims to discover if self-defined tone deaf people show any pattern of musical difficulties relative to controls, and to offer possible explanations for them ( e.g. perceptual, cognitive, productive, motivational). 13 self-reporting “tone deaf” (TD) and 17 self-reporting “not tone deaf” (NTD) participants were assessed on a range of measures for musical perception, cognition, memory, production and self-ratings of performance. This paper reports on four measures to assess perception (Montreal Battery of Evaluation of Amusia), vocal production (songs and pitch-matching) and self-report. Results showed that the TD group performed significantly less well than the NTD group in all measures, but did not demonstrate the dense deficits characteristic of “congenital amusics”. Singing performance was influenced by context, with both groups performing better when accompanied than unaccompanied. The TD group self-rated the accuracy of their singing significantly lower than the NTD group, but not disproportionately so, and were less confident in their vocal quality. The TD participants are not facing an insurmountable difficulty, but are likely to improve with targeted intervention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".