Date of Award

Spring 2021

Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Cohn, Richard


This dissertation isolates, defines, and explores the phenomenon of Motive-Directed Meter (MDM), which has hitherto received little scholarly attention. MDM is a listening experience evoked by music that is temporally regular enough to encourage metric listening and prediction, but irregular enough to frustrate these behaviors. MDM arises when recurring musical motives suggest parallel metric hearings, but shifting durational spans make metrical parallelism difficult to achieve. Listeners are therefore caught in a state of expectational limbo, urged to continually revise predictions that are recurrently thwarted. To approach this phenomenon, Chapter 1 describes the model of musical meter that undergirds this project, in which meter is viewed as an experiential process of temporal orientation taking place in the mind and body of a listener. Central to this dissertation is the notion that, like temporal orientation itself, the category “metric music” is not binary but graded, permitting degrees of inclusion; this removes the need to determine whether MDM can be considered “metric.” In order to accommodate this fluid conception, a flexible model of meter is introduced, which assesses the entrained listening experience according to four continua: timepoint specificity, pulse periodicity, hierarchic depth, and motivic saturation. These criteria are combined to create the multidimensional Flexible Metric Space, which accommodates all metric experiences, including Motive-Directed Meter, traditionally deep meter, and any other listening experience arising from synchronization with felt pulsation. This graded approach to membership in “metric music” allows analysts to compare and contrast musics from diverse repertoires. After Chapter 1 defines Motive-Directed Meter and the model of meter in which it is situated, Chapter 2 introduces five analytic tools appropriate to MDM. Some of these are adapted, some are newly developed, and each captures a different aspect of real-time listening. First, motive maps provide visual representations that summarize and highlight relationships between motives and durational spans, providing an overview of the interplay between these domains. Second, the variability index ranks categories of meter according to entrainment difficulty in isolation. Taken together, these two methods provide a rough picture of the shifting levels of unpredictability across a given passage of MDM. Third, Mark Gotham’s metric relations describe the relative difficulty and quality of connections between adjacent meters, further refining the processual approach undertaken here. Fourth, the metric displacement technique assesses the degree of mismatch between a listener’s expectations and realized musical events, comparing the expected metric depth—roughly, the metric strength—of certain important musical events with the “actual,” realized metric depth of those moments. This technique thereby describes the magnitude of the entrainment shift a listener must undertake in order to adjust to musical events at unexpected temporal positions. Fifth and finally, three expectation-generation methods are used to produce hypothetical sets of predictions intended to roughly approximate listener expectations at various stages of the learning process; these are local inertia, motivic inertia, and prototype methods. The utility of these analytic techniques is highlighted by way of a diverse series of analyses. Chapters 2 and 3 focus on the music of Igor Stravinsky: Chapter 2 analyzes brief passages from the Rite of Spring, the Soldier’s Tale, and Petrushka, while Chapter 3 delves deeply into three large works: the “Sacrificial Dance” and “Glorification of the Chosen One” from the Rite of Spring, and the “Feast at the Emperor’s Palace” from the Song of the Nightingale. Chapter 4 then moves beyond Stravinsky to explore the music of a large number of late twentieth- and early twenty-first century composers and popular music artists working in diverse styles and genres. The artists studied in this chapter include the composers Meredith Monk and Julia Wolfe, and the groups Rolo Tomassi and Mayors of Miyazaki. The analyses comprising this dissertation employ an experiential perspective, combining the techniques outlined above in order to better understand how we as listeners may work to orient ourselves to these pieces of music. In contrast to traditional structuralist approaches, all of the analyses presented in chapters 2-4, as well as the tools supporting them, are directed at the listening experience. Indeed, this dissertation—from its conceptions about meter and the tools it introduces, to the analyses that stem from both—is driven by a belief that the experience of the listener must lie at the heart of the analytic process. Central to all of the analyses is thus this aim: to illustrate how Motive-Directed Meter arises and to elucidate what it feels like to listen to it. With hope, this experience-driven approach may serve as a starting point for others seeking to similarly represent musical meter.