Abstract
Many human behaviors are discussed in terms of discrete categories. Quantizing behavior in this fashion may provide important traction for understanding the complexities of human experience, but it also may bias understanding of phenomena and associated mechanisms. One example of this is absolute pitch (AP), which is often treated as a discrete trait that is either present or absent (i.e., with easily identifiable near-perfect "genuine" AP possessors and at-chance non-AP possessors) despite emerging evidence that pitch-labeling ability is not all-or-nothing. We used a large-scale online assessment to test the discrete model of AP, specifically by measuring how intermediate performers related to the typically defined "non-AP" and "genuine AP" populations. Consistent with prior research, individuals who performed at-chance (non-AP) reported beginning musical instruction much later than the near-perfect AP participants, and the highest performers were more likely to speak a tonal language than were the lowest performers (though this effect was not as statistically robust as one would expect from prior research). Critically, however, these developmental factors did not differentiate the near-perfect AP performers from the intermediate AP performers. Gaussian mixture modeling supported the existence of two performance distributions-the first distribution encompassed both the intermediate and near-perfect AP possessors, whereas the second distribution encompassed only the at-chance participants. Overall, these results provide support for conceptualizing intermediate levels of pitch-labeling ability along the same continuum as genuine AP-level pitch labeling ability-in other words, a continuous distribution of AP skill among all above-chance performers rather than discrete categories of ability. Expanding the inclusion criteria for AP makes it possible to test hypotheses about the mechanisms that underlie this ability and relate this ability to more general cognitive mechanisms involved in other abilities.
Highlights
In psychological science, human behaviors are sometimes quantized to a small number of discrete categories, often reflected as the simple presence or absence of an ability
A Gaussian mixture modelling analysis strongly suggested that genuine-absolute pitch (AP) and pseudo-AP are merely gradations of the same ability, rather than representing discrete abilities as previously argued
While the onset of musical training, do differentiate subjects with at-chance performance from subjects with above-chance pitch labeling ability, these factors do not seem to have a statistical relationship with gradations of absolute pitch-labeling ability
Summary
2.1 ParticipantsWe received a total of 195 unique responses (assessed by IP address) to the online AP assessment. If multiple responses were associated with a single IP address, we selected the earliest response from each IP to isolate a single respondent. While this culling may appear overly conservative, it should be noted that virtually all the duplicate responses (92.9%) were associated with high levels of note identification accuracy (>80%), suggesting that individuals who performed well were more likely to repeat the measure. Half of the 195 participants (48.6%) completed the study within a one-week period (from June 11, 2017 to June 16, 2017). We attribute this spike in participation to a Wall Street Journal article published on June 11, 2017 [21] that provided a link to the online study
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