Imprecise singing is widespread
Bibliographic record
Abstract
There has been a recent surge of research on the topic of poor-pitch singing. However, this research has not addressed an important distinction in measurement: that between accuracy and precision. With respect to singing, accuracy refers to the average difference between sung and target pitches. Precision, by contrast, refers to the consistency of repeated attempts to produce a pitch. A group of 45 non-musician participants was asked to vocally imitate unfamiliar 5-note melodies, as well as to sing a series of familiar melodies from memory (e.g., Happy Birthday). The results showed that singers were more accurate than they were precise, and that a majority of participants could justifiably be categorized as imprecise singers. Accuracy and precision measures were correlated with one another, and conditional-probability analyses suggested that accuracy predicted precision more so than the converse. Finally, performance differences across groups of singers were greater for the imitation of unfamiliar tone sequences than for the recall of familiar melodies.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".