Ecological Models of Musical Structure in Pop-rock, 1950–2019

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

By

Nicholas J. Shea, M.A., B.Ed. Graduate Program in Music

The Ohio State University 2020

Dissertation Committee: Anna Gawboy, Advisor and Dissertation Co-Advisor Nicole Biamonte, Dissertation Co-Advisor Daniel Shanahan David Clampitt

Copyright by Nicholas J. Shea 2020 Abstract

This dissertation explores the relationship between guitar performance and the functional components of musical organization in popular-music songs from 1954 to 2019.

Under an ecological theory of affordances, three distinct interdisciplinary approaches are employed: empirical analyses of two stylistically contrasting databases of popular-music song transcriptions, a motion-capture study of performances by practicing musicians local to

Columbus, Ohio, and close readings of works performed and/or composed by popular- music guitarists. Each offers gestural analyses that provide an alternative to the object- oriented approach of standard popular-music analysis, as well as clarification on issues related to style, such as the socially determined differences between “pop” and “rock” music.

ii Dedication

To Anna Gawboy, who is always in my corner.

iii Acknowledgments

Here I face the nearly insurmountable task of thanking those who have helped to develop this research. Even as all written and analytical content in this document is my own,

I cannot deny the incredible value collaboration has brought to this inherently interdisciplinary study. I am extremely fortunate to have a small team of individuals on which I can rely for mentorship and support and whose research backgrounds contribute greatly to the domains of this document.

Foremost, I express my continuing gratitude to my advisor Anna Gawboy. When I first arrived at Ohio State, I presented her with a hunch I had about the relationship between guitar performance and the functional organization of rock music, along with a rough plan to investigate it more thoroughly. It is through her decisiveness and acumen as a mentor that the project came to fruition, as she wrote countless letters of support for grants, edited my proposals, and challenged me to think more carefully about the real-world implications of my work. Where others were skeptical or hesitant about the project’s reach, her unwavering support gave me the encouragement to maintain that this line of research is indeed worth pursuing (even if we both consistently refer to it as “ambitious”). It is a testament to her mentorship that I was able to conduct the following theoretical, empirical and behavioral analyses over the course of two short years post candidacy.

Daniel Shanahan’s contributions to the project are also difficult to quantify. Even before his official arrival at OSU, Dan has likewise been in full support of my research: offering materials and thoughts on methodology over countless cups of coffee, connecting me with individuals such as Craig Sapp, pushing me to be more precise in the scientific aspects of the project, describing the merits of Bayesian statistics, and editing grant

iv applications. Dan, in many ways, embodies the ideal interdisciplinary music researcher. This is something to which I aspire now and in future work. My thanks to him and his open door.

Nicole Biamonte’s research on rock music acts as one of the earliest influences on this study, as I find her work exemplifies the intersection of theory and practice in popular- music analysis. Her direct support as a co-advisor for the dissertation has likewise been invaluable. Aside from keen edits and a consistent stream of resources and readings to consider, Nicole brings an unmatched specialization to the study—an expertise formative in my attempts to bridge schools of musical thought. I find it difficult to imagine the shape of this project without her contributions.

There are of course many others to recognize: David Clampitt for his edits to this document, enriching coursework, and regular meetings about my progress; Christopher

White for his continuing mentorship since my time at UMass Amherst; Ian Quinn, Jonathan

De Souza and Michèle Dugay for their feedback at various stages of the project; Craig Sapp for the timely and generous development of the project’s Humdrum component; Leo

Glowacki for developing the R and Python code for the initial analysis at SMPC (and for teaching me about global variables); Oded Huberman and Vita Berezina-Blackburn for their guidance crafting the motion-capture rig; student corpus encoders Tristan Collins, Hannah

Moore, Cooper Wood and Sarah Nichols; and of course my friends in the music cognition lab, Sammy Gardner, Sam Burgess, and Lindsey Reymore. To Lindsey, in particular, I am very grateful for her camaraderie during this past year.

I close by offering my love and thanks to my family; my parents Trice, Jack and

John, and siblings Brendan and Tabitha for their support from afar; and finally, to my partner Abigail, who continues to extend me nothing but patience, love and grace.

v

Vita

2013 B.M. Music Education, University of Missouri-St. Louis

2017 M.A. Music Theory, University of Massachusetts Amherst

2017–2020 Graduate Teaching Associate, Music Theory, The Ohio State University

2020 Assistant Professor of Music Theory, Arizona State University

Fields of Study

Major Field: Music

vi

1. Table of Contents

Page

ABSTRACT ...... II DEDICATION ...... III ACKNOWLEDGMENTS ...... IV VITA ...... VI FIELDS OF STUDY ...... VI LIST OF FIGURES ...... IX CHAPTER 1: INTRODUCTION ...... 1 Structure of the document ...... 3 Stylistic Terminology ...... 6 Use of Statistics ...... 8 CHAPTER 2: INSTRUMENTS AND STYLE ...... 9 Multi-modal Perceptual Symbols ...... 9 Instruments of Music Theory...... 13 Producers and Style ...... 15 Surface-level Features and Perception ...... 22 Multi-modal Function ...... 25 CHAPTER 3: GESTURE AS FUNCTION IN ROCK ...... 28 Affordances ...... 31 Analysis: Affordances in “All Day and All of the Night” ...... 34 Five principles of rock guitar performance ...... 39 A Cartesian Model of Guitar Performance ...... 41 Function of Open Strings ...... 44 Instrument Distinction in Functional Analysis ...... 51 STYLISTIC FEATURES OF MODAL ROCK SONGS ...... 55 Biamonte Modal-Pentatonic Corpus ...... 55 Materials and Method ...... 56 Harmony: The Surface of Rock Music ...... 62 Form: Function and Performance Practice ...... 73 Predicting Changes in Form ...... 78 Caveats and Future Work ...... 83 Summary and further application ...... 87 CHAPTER 4: STYLISTIC GROUND TRUTH IN POPULAR MUSIC ...... 88

ACCESSIBILITY IN METHODOLOGY ...... 89 Pop-rock Features Corpus ...... 93 Pop-rock Function Corpus ...... 96 Diversity in Sampling ...... 97

vii

Demographic Encoding ...... 101 File Format and Feature Extraction ...... 105 FUNCTION CORPUS ...... 106 Form Encoding ...... 106 Descriptive Statistics ...... 109 STYLE AND PERFORMANCE PRACTICE IN THE FUNCTION CORPUS ...... 114 Parsimony and Harmony: Harmonic Patterning ...... 114 Formal Characteristics ...... 120 DISCUSSION ...... 122 CHAPTER 5: AFFORDANT PRESSURES ON GUITAR PERFORMANCE PRACTICE ...... 124

STUDY: MOTION-CAPTURE AND STYLE ...... 127 Hypotheses ...... 127 Materials ...... 127 Method: Motion Capture ...... 130 Participants ...... 132 Method: Performance and Recording...... 132 Cleaning the Data ...... 135 Descriptive Statistics and General Observations ...... 137 RESULTS ...... 147 Test 1: Formal Function ...... 147 Test 2: Harmonic Function ...... 148 Test 3: Fitts’s Law...... 151 DISCUSSION ...... 153 CHAPTER 6: DISSONANCE TREATMENT AND PERFORMANCE PRACTICE IN “PARIS IS BURNING” BY ST. VINCENT ...... 155 General Formal Organization and Tonal Frame ...... 158 THE MELODIC-HARMONIC DIVORCE ...... 159 FUNCTION AND PERFORMATIVE-THEMATIC UNITY ...... 167 Prechorus ...... 168 Chorus ...... 172 Performative and Narrative Unity ...... 175 STYLE AND PRACTICE ...... 176 CONCLUSION ...... 180 Summary ...... 186 Future Work ...... 187 BIBLIOGRAPHY ...... 189 APPENDIX A: THE BIAMONTE MODAL-PENTATONIC CORPUS ...... 197 APPENDIX B: THE POP-ROCK FUNCTION CORPUS ...... 202 APPENDIX C: PERFORMANCE DATA FROM MOTION-CAPTURE EXPERIMENT ...... 221

viii

List of Figures

Figure 3.1. de Clercq and Temperley’s analysis of “Hey Jude,” beginning of the bridge, under competing tonal centers...... 29

Figure 3.2. Topographical distance in McCartney’s arpeggiation of the C major chord, physical centering around F, and functional shift to restart the phrase...... 30

Figure 3.3. Fretboard map of internal and cross-formal transitions in Dave Davies’s performance of “All the Day and All of the Night” by The Kinks...... 38

Figure 3.4. Two voicings of a three-note C7 chord in fretboard space...... 44

Figure 3.5. Transcription of main riff in “Crazy On You” by Heart, composed/performed by Nancy Wilson...... 46

Figure 3.6. Open strings substitution of previous note’s fret position to better-model performative distance in “Crazy On You” riff...... 47

Figure 3.7. Transcription and harmonic reduction of main riff in “I Believe in a Thing

Called Love” by The Darkness, composed and performed by Dan Hawkins...... 48

Figure 3.8. Pitch/fret proximity in the primary riff of “I Believe in a Thing Called Love” by

The Darkness, composed and performed by Dan Hawkins. The hand is centered on F#. ... 49

Figure 3.9. Video analysis of form and gesture in “I Believe in a Thing Called Love.” (Click icon above to view on my personal website. Video will be first on the page.) ...... 50

Figure 3.10. The eight harmonic states of the McGill-Billboard corpus divided by style: a primary (T, S), minor mode (P, Q) and jazz (W, X) circuit. From White and Quinn 2018. .. 54

Figure 3.11. Tablature formats, “Crazy Little Thing Called Love” by Queen, verse...... 59

Figure 3.12. Frequency of inversionally equivalent bass pitch transitions in the Modal-

Pentatonic corpus...... 65 ix

Figure 3.13. Frequency of directional bass-pitch transitions in the Modal-Pentatonic corpus.. 66

Figure 3.14. Frequency of directional bass pitch transitions in Modal-Pentatonic corpus...... 67

Figure 3.15. Ascending minor thirds in “Radar Love” by Golden Earring...... 70

Figure 3.16. Descending minor thirds, “Everybody’s Got Something to Hide (Except for

Me and my Monkey)” by The Beatles...... 70

Figure 3.17. Open-string ascending minor thirds, “Love Me Two Times” by The Doors. .. 71

Figure 3.18. Open-string descending minor thirds in the guitar part of “Break on Through” by The Doors...... 71

Figure 3.19. Top-eight most-frequent pitch transitions modeled by fingering on a guitar fretboard...... 74

Figure 3.20. Stylistic components of the Modal-Pentatonic corpus by formal section (inter- formal transitions only). Asterisks note an above-average rate of performative transitions. .. 75

Figure 3.21. Density of note-to-note pitch distances in the Biamonte Modal-Pentatonic corpus...... 79

Figure 3.22. Density of note-to-note Euclidean distances in the Biamonte Modal-Pentatonic corpus...... 80

Figure 3.23. The generalized linear mixed-effects model considers the Euclidean and pitch distance values calculated by the pitch transition over the double bar, from verse to chorus.

“Crazy On You,” by Heart...... 82

Figure 3.24. Generalized linear mixed-effects model to predict moments of formal transition via Euclidean and pitch distance, with the random variable of a metric gap between notes in the Modal-Pentatonic corpus...... 83

x

Figure 3.25. Comparison of historical distribution between Guitar Pro files archived on ultimate-guitar.com and the encoded songs in the McGill-Billboard and Rolling Stone 200 corpora.

...... 86

Figure 4.1. Density of Euclidean (performative) distance in the Function corpus...... 110

Figure 4.2. Density of directional (non-mod) pitch distance in the Function corpus...... 111

Figure 4.3. Transition probabilities by form in the Function corpus (n = 433 songs)...... 113

Figure 4.4. Pitch transitions by style in the Function corpus ...... 116

Figure 4.5. Top 5% of harmonic transitions in the Function corpus sample (n = 200 songs) modeled on an abstract fretboard by fret distance. Grey nodes represent instances where transitions occur proportionally more frequently in a pop style than in a rock style. White nodes represent the reverse...... 118

Figure 4.6. Most frequent types of bass-pitch transitions by style in the Function and Modal-

Pentatonic corpora...... 121

Figure 4.7. Generalized linear mixed-effects model to predict moments of formal transition via Euclidean and pitch distance, with the random variable of a metric gap between notes in the Function corpus...... 122

Figure 5.1. Motion-capture rig, materials and cost...... 128

Figure 5.2. Symmetrical chord progression used in all conditions...... 130

Figure 5.3. Performer left hand with pink tape on index finger (A) and motion-capture frame (B). The box tracks the color pink to approximate hand centering and reports coordinates...... 131

Figure 5.4. Garage Band drumbeat presets and waveform used in the performance task. 134

Figure 5.5. X-axis transitions over time, pop 90 bpm...... 138

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Figure 5.6. X-axis transitions over time, rock 90 bpm...... 139

Figure 5.7. X-axis transitions over time, pop 120 bpm...... 140

Figure 5.8. X-axis transitions over time, rock 120 bpm...... 141

Figure 5.9. Y-axis transitions density, pop 90 bpm...... 143

Figure 5.10. Y-axis transitions density, rock 90 bpm...... 144

Figure 5.11. Y-axis transitions density, pop 120 bpm...... 145

Figure 5.12. Y-axis transitions density, rock 120 bpm...... 146

Figure 5.13. Generalized linear mixed-effects models for hypermetric and formal transitions...... 148

Figure 5.14. Density of Euclidean distance, fourth-based progression...... 150

Figure 5.15. Density of Euclidean distance, third-based progression...... 150

Figure 5.16. Box plot of Euclidean distance by progression type...... 151

Figure 5.17. Box plot of Euclidean distance by bpm...... 152

Figure 6.1. Transcription of Melody, guitar, and bass parts, verse, “Paris is Burning,” 0’ 18’’

...... 159

Figure 6.2. Pitch-space reduction of voice leading in the guitar part starting from the root, verse, “Paris is Burning.” Each quarter note represents one chord in the verse’s harmonic cycle...... 161

Figure 6.3. Voice-leading reduction of melody and guitar and bass parts, verse, “Paris is

Burning,” 0’ 18’’ ...... 164

Figure 6.4. A fretboard network of chord transitions, verse, “Paris is Burning,” 0’ 18’’. ... 165

Figure 6.5. Transcription of melody, guitar and bass parts, prechorus, “Paris is Burning,” 0’

41’’...... 168

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Figure 6.6. Transcription of guitar part in tablature notation, prechorus to chorus, “Paris is

Burning,” 0’ 41’’ to 1’ 07’’...... 169

Figure 6.7. Fretboard network of harmonic transitions, prechorus to chorus, “Paris is

Burning,” 0’ 41’’ to 1’ 07’’...... 170

Figure 6.8. Transcription of vocal and guitar part, chorus, “Paris is Burning,” 1’ 09’’...... 172

Figure 6.9. Transcription of guitar part, chorus, “Paris is Burning,” 1’ 09’ ...... 174

Figure 6.10. Gradual harmonic, melodic, and narrative-perspective unification across the forms of “Paris is Burning.” ...... 177

Figure 6.11. Primary keyboard riff of “Hold the Line” by Toto, composed by Paich...... 183

Figure 6.12. Primary riff for “Hold the Line” by Toto, composed by David Paich. The graph below demonstrates the number of half-step transitions from chord to chord...... 185

xiii 1. Chapter 1: Introduction

Brittany Howard—guitarist, vocalist and songwriter for Alabama Shakes and, more recently, solo artist—echoes a sentiment common amongst popular music artists: “I got my education just listening to records… I don’t really care about chords” (Reyna 2017).1

Howard instead outlines how her experiences growing up Black and poor in rural Alabama shape her characteristic sound. In the interview, she describes how she approaches the guitar through physical gesture (“the eagle claw”) and remarks often on the stylistic influence of other artists (“the James Brown chord”). Due to her perceived lack of training, she also describes herself primarily as a songwriter, rather than a vocalist or guitarist.

Despite downplaying her virtuosity as a performer, Howard highlights that her guitar is a primary tool in her songwriting process:

The feel of the guitar—first thing’s first. Like, let’s say I’m at a guitar store…alright, it feels good but let’s see if it passes the test—hook it up to a shitty amp, but does it still have any character at all… Can I play it fast? Can I play it well? Does it sustain well? Does it have a nice woody tone? Is it natural? Can it be timeless?…It’s all about having those sounds that speak to me and inspire me to want to write a song with it.

The physical nature of the instrument, its playability, is clearly important to Howard. But nearly any time she discusses a specific physical technique, she frames it as pursuant to a characteristic sound. As she describes, she is “more interested in knowledge and knowing how to play different types of music.” These characteristic sounds, conveyed through her

1 See Reyna’s article “Brittany Howard on Collaboration, Gear, and Making Up Your Own Chord Shapes,” in She Shreds: (https://sheshredsmag.com/brittany-howard-11/).

1 electric guitar, evoke the timbres and textures of her favorite artists, including James Brown,

Dave Davies of The Kinks, David Bowie and Jimi Hendrix. Her multi-modal approach to songwriting—using an instrument to explore and emulate the creative output of other artists—is likewise typical of popular-music artists.2 Such an approach is perhaps a necessity for Howard, due to the barriers she faced on her path to musicianship.

To what end is there room in popular music analysis for considering Howard’s priorities as a songwriter and performer? That is, where is agency granted to artists as performers and songwriters when discussing its structural and stylistic development? Two emerging areas of music research are noteworthy for foregrounding the cognitive and physical domains of music making: Barsalou’s theory of perceptual symbols (Zbikowski

2017) and critical organology (Rehding 2016). Temperley (2004) and Meyer (1989) similarly provide an effective frame for delineating issues in style analysis and transmission, thus offering a method for contextualizing the immediacy of sound production with social influences. This document intersects these methodologies to approximate and give due credit to the cognitive-physical and stylistic pressures that enact on artists as they produce popular music.

Howard’s remarks on her own compositional strategies parallel those often discussed in scholarship on Western European common-practice music. For example, Hepokoski and

Darcy (2006) characterize a composer’s development of a sonata in a manner similar to

Howard’s own account of her songwriting process. The authors note: “Surely the most common decisions were made efficiently, expertly, and tacitly on the basis of norms that had

2 Other self-trained artists include Louis Armstrong, Richard Wright (Pink Floyd), Prince, and Jimi Hendrix.

2 been internalized (rendered automatic) through experience and familiarity with the style” (9, emphasis mine). Even though the formal stylistic components between popular music and

Western European art music are disparate (especially harmonic practice), this dissertation argues that the only obstacle between making equivalent their compositional practice is to consider a producer’s priorities. That is, for Haydn, Mozart, and Beethoven, their compositional tools include a relatively standardized model of harmonic function and a tacit or socially determined understanding of formal process. For popular-music artists, similar pressures of style are evident, especially in regard to form (Summach 2012). But in harmonic practice, the evidence I provide in the following chapters suggests that much of popular music’s characteristic harmonic grammar develops not solely from the constraints of a standardized harmonic paradigm, but from the physical and tonal constraints of an instrument in tandem with the components of musical style. As I demonstrate, this perspective—composing from the instrument—aligns with first-hand accounts by practicing popular music artists. These artists and their performative experience, I argue, are key to understanding harmony, form, texture and timbre as the formal-stylistic components of popular music.

Structure of the document

In the following chapters, I establish a methodological precedent for considering how the lived experiences and priorities of performers and composers, as practitioners of popular music, provide alternative but compelling perspectives on the stylistic-functional organization of popular music. By prioritizing musicians as human agents of musical

3 development, I aim to encourage music theory as a discipline to consider what is lost when avoiding issues of sound production in popular-music scholarship, while demonstrating the value that non-traditional paths to musicianship offer to popular music’s most pervasive analytical issues.

In chapter 2, I outline Barsalou’s theory of perceptual symbols in application to guitar performance. The guitar, treated as an instrument of music theory, acts as a cognitive frame for musical decisions made by the performer or composer. These decisions are relayed as matters of style and function, with the understanding that various musical objects (e.g., a chord) and performative actions (e.g., a gesture) hold contrasting roles depending on a style or genre (e.g., popular music, Western European art music, pop, rock, etc.). Under an ecological theory of affordances, factors of physical performance, stylistic preferences, and a musician’s experience and training are framed as “communicative pressures” (Temperley

2004, 314) on the development and transmission of popular music’s surface-level and structural elements. I then use Temperley’s model to synthesize formalist and social methods of style analysis to expand to expand Meyer’s (1989) model toward the twenty-first century.

In chapters 3 and 4, I use two corpora of popular music transcriptions to illustrate the analytical utility of a gesture-as-function model of guitar performance practice. The first corpus is a collection of modal-pentatonic rock songs, called the Biamonte Modal-Pentatonic

Rock corpus. These guitar-driven songs, with their relatively uniform harmonic and formal organization, relay how guitarists generate rock’s harmonic language by maintaining inter- formal fretboard parsimony, distinguish formal sections by gestural activity, and articulate formal changes with pronounced gestures.

4

Chapter 4 outlines the development of the Pop-rock Function corpus. With this corpus,

I investigate to what extent gestural principles apply to a more stylistically and historically diverse collection of songs, in an effort to determine how performers and songwriters understand and articulate the often-elusive differences between “pop” and “rock” as socially determined genres of popular music. The Function corpus is also formed in the spirit of inclusion, featuring a balanced collection of works by mainstream artists in addition to those traditionally underrepresented in analysis; namely, women and minority songwriters and performers.3 Each corpus is made accessible to the public through an online database. This allows other analysts to easily access songs by these mainstream and marginalized artists, as well as search for and study the various components of style (e.g., formal organization, rhythmic complexity, instrumentation, etc.).

Because corpora are in a sense a collection of musical objects, unsubjected to the real-time pressures of performance, chapter 5 offers a motion-capture study to test the application of the gesture-as-function model in real time. There, performances by local practicing musicians frame investigations into formal, stylistic and social influences on guitar performance practice. The chapter also provides detailed instructions for other music researchers to develop and use the study’s low-cost motion-capture rig in their own studies on gesture.

The final chapter, chapter 6, is perhaps the most theoretical in nature, synthesizing the previous chapters’ findings on style and performance practice in a close reading of “Paris

3 The use of the word “minority” in this and future contexts specifically refers to any artist or group of artists whose identity is subject to marginalization. These include the characteristics or practices of race, ethnicity, religion, sexual orientation, or disability (Laurie & Khan 2017). I address this in greater detail in chapter 4. 5 is Burning” by Annie Clark, the artist known St. Vincent. Clark’s background as a Berklee- trained musician, versed in (but occasionally resistant to) common-practice models of harmony and voice-leading, provides a unique opportunity to investigate how her roles as an expert listener, performer and songwriter intersect to generate a musical texture that is evocative of rock, pop, and common-practice conventions of musical organization.

Stylistic Terminology

As is the case with previous studies on popular music, it is pertinent to outline the parameters for the terms “popular music,” “pop,” and “rock” as they occur throughout the document. My use of the term “popular music” refers to music that is either commercially successful, critically acclaimed, and/or made accessible to the general public from the years ca. 1950 to the present. This synthesis of parameters is due largely to the proliferation of modern music streaming services such as Spotify, where popular music’s scope expands well beyond that of many longitudinal popular music databases such as the Rolling Stone 200 (de

Clercq and Temperley 2011) and the McGill-Billboard Hot 100 database (Burgoyne 2011). My stylistic scope is also shaped by the database from which I draw—a collection of high-quality transcriptions of popular music songs archived on the website ultimate-guitar.com. As such, I do not personally attempt to constrain or define what genres constitute popular music, but instead focus on works that fall under the commonly employed bisection of popular music into “pop” and “rock” styles as provided by the ultimate-guitar.com database.4 This

4 I do, however, limit the inclusion of certain song types, such as theme songs from television shows and movies or popular classical music. A list of representative songs can be found in Appendix B.

6 juxtaposition between “pop” and “rock” as socially determined stylistic parameters reflects the title of the dissertation.

In music-theoretic literature, the use of these terms is somewhat contentious. de

Clercq (2017), de Clercq and Temperley (2011), Nobile (2014, 2016), Stephenson (2002), and

Everett (2004) follow the precedent set by Moore 1992 (or perhaps earlier) for treating the term “rock” as a catch-all for commercially successful Anglophone music from the 1960s to the 1990s. Others, such as Biamonte (2010) are perhaps more specific in their treatment:

Biamonte’s use of “rock” refers specifically to the “classic rock canon” which, like Nobile

(2014), may include some “pop” songs, but largely focuses on specific genres such as “hard rock, and progressive rock” (95). On the other hand, scholars are even less clear about what constitutes “pop” music. Of interest to this study is Nobile’s assessment that “by the late

1970s, ‘pop’ referred to keyboard-based music while ‘rock’ referred to guitar-based music”

(244). As I illustrate in the following chapters, the relationship between the physical- harmonic structure of the electric guitar and its characteristic timbres are important factors in style distinction.

Overall, where Nobile (2014) finds the term “popular music” as “too-broad” (8), I see it as wholly appropriate for the focus of this dissertation. Again, this is due largely to the database from which I draw—songs from ultimate-guitar.com—and my historical scope (ca.

1950–2019). Specifically, each archived song coordinates with metadata that includes genre or style information. By utilizing this data, I avoid positioning myself in a stylistic camp of

“popular music,” “rock” or “pop-rock” and instead rely on labels provided by others to

7 assess the performative, formal and harmonic aspects of “pop” and “rock” music as socially

(not theoretically) determined stylistic categories.

As a final note on terminology, the document also frequently draws comparisons between popular music and Western European art music ca. 1700–1900. For efficiency I simply use the term “common-practice music” to refer to the latter throughout. However, in using the term I do not attempt to define which composers or decades are included in common-practice music, but rather most often employ the term to refer to music theory’s historically main repertoire of focus (e.g., the European tonal music which includes, but is certainly not limited to, composers Bach to Brahms).

Use of Statistics

Due to the inherently interdisciplinary nature of music research on style and performance practice, this dissertation often interleaves hermeneutic and empirical analysis.

Occasionally, and especially in chapters 3 and 4, I employ statistical models to illustrate relationships between musical variables (e.g., pitch, gestural distance, form) and evaluate their significance. I attempt to present these models in a straightforward and accessible manner, defining the utility of models and the meaning of terms (e.g., correlation, probability) when they occur. In these cases, I do follow traditional scientific convention when offering statistical values, such as probabilities. In doing so, I aim to highlight the interdisciplinary value of humanities- and empirical-based methods of musical analysis, while also upholding the document’s commitment to accessibility by not requiring prior knowledge of statistics.

8

2. Chapter 2: Instruments and Style

Multi-modal Perceptual Symbols

The power of a perceptual symbol comes from its ability to evoke complementary perspectives on the same object (Barsalou 2005; Zbikowski 2017, 34). Zbikowski illustrates the musical utility of Barsalou’s theory of perceptual symbols with the example of a perfect authentic cadence (PAC). He states that when a person imagines or “simulates” a PAC, they necessarily do so in various modalities: mentally hearing or audiating (Karpinski 2001) the auditory stream, performing the event on an instrument, and responding emotionally and/or physically to the progression. For classically trained musicians, the category of a “PAC” also shares an association with other categories, such as the imagined sound and physical feeling of scale-degree 7 in the dominant “pulling” toward scale-degree 1 of the tonic. In this way, the PAC is a “simulator” or a cognitive-categorical object that evokes dynamic sensory and perceptual responses to an otherwise non-physical object.5

Zbikowski’s example of the PAC highlights the innate compatibility of formalist (i.e., symbolic) and embodied (i.e., experiential) perspectives as tools for enhancing musical understanding. Multiple examples of this intersection, particularly between theory and performance practice, pervade in music theory. Klorman (2016), for example, describes

5 As Barsalou (2005, 398) explains, when presented with a stimulus, neurons in the human brain fire to produce a sensory representation of the object which are then stored as a cluster of conjunctive neurons within an association area. When the same object is later reimagined or simulated, this process is reversed, where clustered neurons in the association area fire to recreate the original mapping of neurons created by the initial stimulus. Barsalou uses a chair as a physical object in his example, but Zbikowski (2017, 33) expands Barsalou’s model, arguing that sounds can act as sonic analogs for physical objects, where the brain fires the same associative neurons for physical objects when presented with a musical stimulus, thus facilitating metaphor and meaning through music. 9 harmonic and formal processes in Mozartean chamber works from the perspective of members of an eighteenth-century string quartet. Each member acts as a respective agent of musical development, fulfilling their own social-performative role within the ensemble.

Klorman also assumes the imagined performers to have an implicit awareness of the norms of musical structure, due to their experiences and training as practicing contemporary musicians. In sum, Klorman’s musicians, through performance, have a tacit understanding of the stylistic conventions of eighteenth-century music, such as harmony and form.

By this perspective, it is assumed that musical practice begets categorical theoretical knowledge and that practice itself is multi-modal, involving embodied (e.g., physical, social, emotional) responses to musical action. In studies on Western European common-practice music, intersections between theory and performance have become somewhat common.

However, this was not always the case, especially in the development of music theory as its own field separate from musicology. Examining scholarship from this period reveals a tension between formalist (i.e., theoretical) and performative knowledge that I believe is relevant to popular music analysis as another developing area of music research.

One of the most pertinent examples of conflicting perspectives on musical understanding comes from Cusick (1994), where the author expresses anxieties about the relationship between theory and practice. Cusick refers specifically to a duality in thought— her potentially competing roles as a performer and as a listener/musicologist. She states:

And when I turn to music theory as a tool to help me understand a piece I need to know about, I find that its habitus, too, inclines to focus on music’s fixed, text-like qualities—a focus that seems contrary to my own musicality… (10)

10

Cusick’s observation again points to the multi-modality of musical understanding.6 It also highlights the various roles that humans hold while engaging with music: Cusick is (perhaps first for the purposes of the article) a performer, but also a listener. Throughout the study, she argues that both roles are essential to her identity as a musician and her experiences in both ultimately serve to enhance, not constrain, her work as a scholar and performer.

This is where I argue popular music analysis often falls short of capturing a holistic perspective on the organization of popular music; in its consistent separation of theory and production or, in Cusick’s terms, prioritizing listening over performing. As I show later in the document, I specifically argue that an over-emphasis on the theoretical/listener perspective gives rise to some of music theoretic analysis’s most persistent methodological caveats (especially when applied across styles from common-practice to popular music).7

Support for this claim comes directly from my personal and professional engagement with social circles of popular music guitarists. In these communities, Cusick’s anxieties about identity-based models of musical knowledge manifest consistently. Perhaps the most indicative and authoritative evidence of this trend comes from Steve Vai’s music theory textbook, Vaideology: Basic Music Theory for Guitar Players (2019), where author and renowned pop-rock guitarist Steve Vai directly addresses concerns of theory and practice.

The premise of Vai’s textbook establishes that guitarists often have a complicated relationship with the “academics” (his term) of music theory (5). Vai sorts guitarists’

6 In parsing this quote I by no means intend to separate the feminist facets of Cusick’s argument from her claims on performance—the topic merely sits outside the focus of this document and Cusick herself does the topic justice enough. 7 These caveats are explored in-depth in chapters 3 and 6.

11 perspectives on theory into three main camps: those who do not hold any regard for theoretical thought but are “powerful music creators nonetheless,” those who are intimidated by music theory, and those who believe that music theory constrains their creativity (5).8 In response to the latter, Vai argues that the “academic” study of music will not necessarily make one a good musician, but it does provide guitarists with a convenient frame for musical understanding. Here, Vai’s language on the subject addresses multi- modality explicitly: “Perhaps the most powerful connective tool to your instrument is the quality of your inner musical ear. This is what manifests the invisible into the physical” (5).

In tandem, his text establishes a bi-modal approach to guitar pedagogy directly in line with

Cusick’s distinction between theorist and performer identities.

Coined “intellectual understanding” and “experiential knowing,” Vai regards fluency in the former as necessity for fluency in the latter (6). Like Barsalou, he speaks of this in terms of modality, arguing that the best way to know or understand the formal organizational components of musical structure is through coordinated practice. But where music theory pedagogues often use the term practice to mean engaging with theory through a variety of activities (e.g., realizing figured bass, singing), Vai specifically (and perhaps exclusively) intends for readers to work through his exercises from the guitar. In doing so,

Vai treats the guitar as an instrument of music theory, which I argue offers an advantageous perspective on popular music, for it addresses physicality as an important but often overlooked influence on the function of music theory’s perceptual symbols.

8 I explore this notion in the conclusion of the dissertation, in light of its results.

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Instruments of Music Theory

Musical instruments serve a “double function” (Rehding 2016) in that they provide a physical and theoretical frame (2.4) for music analysts. Rehding’s investigation of

Pythagoras’s relationship with the monochord reveals this specifically, suggesting that its use as instrument as a tool for performance notwithstanding, that Pythagoras uses the monochord to both create and theorize about sound and music. Because of this, for

Rehding, the monochord fulfills “the essential function of a music-theoretical instrument”

(4.4). Instruments of music theory research falls under a relatively new area of study, but a core group of works reinforce the goals of this dissertation. Each of the following studies specifically highlights how considering the means of production via instruments enhances musical understanding in both common-practice and popular music repertoires.

Gawboy (2009) offers an in-depth perspective on the non-linear physical makeup of the Wheatstone concertina to demonstrate how its Tonnetz-like lattice of fifths and thirds complicates otherwise assumedly simple pitch transformations, such as transposition by octave or step. Her study also reinforces how the symmetrical structure of the instrument’s harmonic system embodies the role of dualist philosophy amongst Victorian Britain’s Royal

Society.

Perhaps unsurprisingly, the piano often acts as an instrument of music theory.

Rehding (2016) obviates the theoretic-practical role of the piano in the music theory classroom, but Hughes (2003) reveals the specific utility of a keyboard perspective in approaching Stevie Wonder’s music. Hughes’s case studies suggest that Wonder, who has been blind since infancy, primarily uses short repeated patterns on the keyboard to develop a

13 sense of groove and flow in his works. Many times, these patterns occur on the black-note tier of the keyboard, giving rise to the pentatonic patterning often heard in Wonder’s music.

Interestingly, the new-age funk band Vulfpeck recently released a video debunking a common misconception related to the performance of Wonder’s hit song “Supersitition,” thus enhancing claims made by Hughes throughout his study.9 The video specifically shows that the G-flat as the melodic peak of the opening of the song’s signature riff is actually relegated to the right hand instead of being played entirely with the left hand. Knowledge of this partitioning reveals an important relationship between pitch, performance, and meter, as each instance of the G-flat occurs on the hypermetric backbeat. In this way, there is a physical alternation between downbeat and backbeat between the hands as the left hand plays the bottom note of the riff in coordination with the bass drum and the top note with the snare. This perspective further reinforces Hughes’s ideas about Wonder’s prioritization of groove and flow, while also making a case for the value of non-academic perspectives on performance practice offered by musicians like Vulfpeck.

Of most relevance to this dissertation are studies that treat the electric guitar as an instrument of music theory (Koozin 2011, De Souza 2018, Capuzzo 2004 and Easley 2015).

I explore many of these articles by in depth in later chapters, but to briefly summarize, each author treats the topographical space of the guitar fretboard as a network or system for articulating physical-musical relationships in practice. Capuzzo focuses specifically on third- related harmonies, primarily in alternative rock songs of the 1990s, and attempts to match these to Neo-Riemannian operations. Koozin and De Souza meanwhile outline the

9 Vulfpeck, “How To Play Superstition Piano Tutorial,” (https://www.youtube.com/watch?v=JA4gC4k67mc).

14 systematicism of fretboard space, as well as its unique features such as pitch recursion, and how these factors influence general practice for fingering choice. De Souza also addresses how performers navigate the horizonal and vertical vectors of the fretboard across other fretted instruments (i.e., not just in electric guitar performance), but this focus is perhaps secondary to his goal of developing a generalized system of fretboard fingering shapes.

Finally, Easley’s study is style-specific, where the author outlines four types of two-part lateral riffs that hardcore rock guitarists use in repetition to generate the style’s harmonic and formal structures.

Producers and Style

An instruments-of-music-theory approach articulates how the physical-tonal constraints performers encounter in practice can shape interpretation. Often, related constraints indicate style. Returning to “Superstition,” Wonder uses pentatonicism as a stylistic-harmonic language specifically because Wonder focuses on a constrained dimension of keyboard space. Similarly, Brittany Howard’s quote from the beginning of the document makes explicit that she uses her guitar to produce, emulate and ultimately communicate various facets of style. In this context, both Wonder and Howard are producers acting in dialogue with stylistic convention. However, it is also important to note that these artists are also both listeners, and experienced ones at that. This duality is similar to, but perhaps different than the one Cusick (1994) paints, as Wonder and Howard not only perform and listen to music, but also at some point create it in real time, again in dialogue with style.

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Style transmission, as a form of musical communication, is the transmission of music’s structural components (e.g., harmony, form) to a listener via audible surface-level features (e.g., pitch, rhythm) as generated by a composer, performer or improviser

(Temperley 2004). This juxtaposition essentially divides the process of musical communication into two groups: producers (e.g., composers, performers), who create surfaces, and consumers (e.g., listeners), who receive structure. In Temperley’s surface-to- structure continuum, each of these parties are subject to what Temperley defines as the

“communicative pressures” of style. One example Temperley provides is the relationship between rubato-syncopation, arguing that common-practice composers use more rubato due to the comparatively sparse use of syncopated rhythms. Conversely, popular music employs more syncopation and is less likely to feature rubato compared to common-practice music due to the former’s stylistic tendency to maintain a consistent tempo, likely brought on by the drumset.

Where studies on style prove advantageous is their capacity for approximating a producer’s priorities in generating a musical surface. Temperley’s essay argues that composers ultimately wish to be understood by the listener and take measured steps to transmit music’s structural elements clearly. To this end, Temperley cites Huron (2001), who demonstrates that parallel fifths and octaves tend to “fuse” together in the auditory domain, which Temperley argues are intervals common-practice music composers avoid so individual notes can be “correctly identified” by the listener. This follows Meyer (1989), who similarly states that physical and psychological constraints (i.e., acoustics and auditory streaming) directly influence music’s compositional makeup.

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Listener perspectives are paramount to nearly any assessment of norms. But what

Temperley’s model and other music-theoretic studies often overlook is that producers are also listeners and thus encounter or engage with a greater number of constraints in production. Like Temperley, Meyer (1989) notes any style is subject to and created by a series of constraints. For example, in Hepokoski and Darcy’s Elements of Sonata Theory, these constraints are what the authors define as paradigms—the most generic framework or compositional components on which sonatas are built.10 To use Meyer’s terms, these paradigms or rules help to define a stylistic period (e.g., eighteenth-century Western

European art music) as they shape compositional process. As composers work within the rules or apply new strategies to work against them, stylistic norms are established. Critically, both sets of authors treat composers as agents in this process, who commonly extend, truncate or repeat musical gestures to reinforce or subvert the expectations of the listener, who through exposure has a implicit knowledge of a sonata’s most generic organizational components.

In popular music analysis, authors such as de Clerq and Temperley (2011) similarly attempt to define how harmony acts as a structural component of musical style. They state, perhaps defensively, that:

…some have argued that rock scholarship has focused excessively on harmony… While we concede this point, it is surely uncontroversial to state that harmony is one important aspect of rock, and that an understanding of this aspect is necessary for a full understanding of the style as a whole (47).

10 Such paradigms include the presence of two themes, the medial caesura, the essential expositional closure (EEC) and the essential structural closure (ESC). 17

While I agree with the authors that harmony is indeed an important feature of style, I argue that it is certainly less so than they make it out to be.11 That is, recent scholarship suggests that harmony does not hold the same structural role in popular music that it is often theorized to maintain in common-practice music.

Studies by White and Quinn (2018), Nobile (2016) and Meyer (1989) support this claim. Each validate through complementary methodologies the notion that harmony in popular music is ultimately diffuse and style-dependent, meaning its functional role is primarily based on syntax (i.e., its relative or positional relationship to other functional musical objects) and not identity (i.e., its unique observable components or characteristics).

Their evidence contradicts de Clerq and Temperley’s study, as well as many others (e.g.,

Nobile (2014), Everett (2008), Stephenson (2002), Moore (1995)), which prioritize chord identity over syntax.

White and Quinn (2018) conduct a lexical analysis of chord transitions in the McGill-

Billboard Hot 100 database (Burgoyne 2011) to find that popular music’s harmonic states are ultimately style dependent. Within they use a Hidden Markov Model (HMM) to evaluate the probabilities of chord transitions throughout the corpus, which the lexical model employs to

11 Biamonte (2010) articulates this issue best in the introduction of her own study on modes and pentatonicism in rock music, observing “Admittedly, this essay’s focus on harmonic structures adds to the problematic emphasis on pitch-based analysis to date (not just in popular-music scholarship) and the comparative neglect of other important parameters such as timbre, texture and sound production, for which analytical tools and methodologies are still being developed” (95). Where I find encouraging value in Biamonte’s study is that she does not assume that there is a one-size-fits-all method for popular music analysis, meaning she understands rock music to hold multiple types of tonal systems which, in the case of modal rock, are perhaps reflective of a particular style. Each of her proposed modal-pentatonic patterns are also relatively constrained, focusing on sequences of two to six chords, which I find more perceptible, utilitarian and agreeable than the large-scale harmonic unfoldings presented in Walter Everett’s work or Temperley’s view of a harmonic grammar under a unified tonal center, as Temperley tends to adapt in de Clercq and Temperley (2011). 18 group chord types into functional categories.12 This process reveals an eight-state harmonic- functional model, where major-mode songs feature four distinct harmony states, while two smaller functional circuits indicate two-state chord transitions in minor-mode and jazz-like songs. Importantly, no a priori assumptions are made about chord function—the model groups chords together without input from the analysts. White and Quinn’s findings are important, for they provide empirical evidence that challenges the widespread application of the three-state Tonic-Predominant-Dominant phrase model, which is typically treated as most appropriate for common-practice works.

In contrast, Nobile (2016) does draw on common-practice three-state model to frame harmonic function in popular music, but ultimately arrives at the same conclusion as

White and Quinn; that syntax drives the perceptible-functional characteristics of chord function. Where Nobile is perhaps more specific than White and Quinn is in Nobile’s use of musical form as a frame for syntactic function. Nobile, like White and Quinn, argues that chord identity should be separated from syntax, pointing to chords such as bVII (e.g., the major subtonic harmony built off of lowered scale-degree 7) and even ii (e.g., the minor supertonic harmony built off scale-degree 2) that aurally act as dominants even though they share no convincing scale-degree relationship with V, the dominant harmony.13 However,

12 White and Quinn’s use of HMMs (317) treats chords as a type of observation generated by a hidden state (i.e., a chord’s function). HMMs use two types of probabilities, lexical and transition, to respectively determine the hidden state itself (to use the ongoing analogy, its functional identity) and the sequence of these states (transition or syntax). The authors cite four necessary components of a HMM: a set of possible states (functions), all possible observations (chords), transition probabilities (syntax) and the probability distribution of the resulting states. 13 I personally find Roman numeral analysis in popular music to be incredibly unhelpful compared to chord- root symbols (e.g., Cm, G7, etc.), given that music theorists as expert listeners still often disagree about the tonal center of a given passage, especially at larger spans or in short harmonic loops. (Such ambiguity is addressed specifically in Richards 2017.) Because of this, I only use Roman numerals in the document when referring to common-practice music, an author’s work where they chose to do so, or when drawing on another 19

Nobile does not discredit chord identity entirely—in his analysis of the “Take Me to the

River” by the Talking Heads, he argues that scale-degree identity does help in hearing the E minor minor-seventh chord at the end of the verse as a syntactic dominant, even in the context of E minor as the home tonic (163).

While Nobile’s and White and Quinn’s approach can easily be criticized for being too subjective (“Any chord can hold any function!”), Meyer (1989) seems to anticipate this trend in harmonic practice. Thus, Meyer would likely agree with the former authors

(especially Nobile) that any chord can provide syntactic closure, due to observed shifts in the frequency of specific harmonic progressions, which Meyer argues leads to the weakening of the “specific syntactic relationships employed by the compositional community” (300).

In his theory of style, Meyer describes three categories of constraints: laws, rules, and strategies. Laws are “transcultural” and include the physical and psychological domains. For example, the gestalt-like features of music are a psychological law, where memory and cognition create unity and hierarchy out of otherwise disjunct events (13). Meyer defines laws by two types of parameters, primary and secondary, which express distinct syntactic features, e.g., the ability to be segmented, provide closure, and express non-uniformity (15). In common-practice music, melody, rhythm, and harmony are fall under the primary category, whereas articulation, dynamics, texture, and timbre are secondary. That is, the former provide closure, while the latter do not. However, Meyer argues that by the end of the nineteenth century, increases in the frequency of previously novel harmonic progressions

author’s methodology, as I do later in chapter 3 with analyses under Biamonte’s modal-pentatonic model of harmonic function. 20

(e.g., a plagal cadence) effectively “flattened” tonal hierarchy, thus elevating the capacity for secondary parameters to provide perceptual closure.

Meyer’s theory about the gradual functional shift between primary and secondary parameters and the impact of statistical exposure also manifest in writings on popular music.

Moore (2012), for example, remarks on the inversion of primary and secondary parameters, stating that rock’s secondary parameters do not merely “shape content [primary parameters]” as typically conceived in common-practice music studies but instead “frequently constitute content” (29, emphasis his) in rock. This is the basis for his conception of the “soundbox” as a three-dimensional methodological space in which to consider texture as a syntactic feature of popular music’s organization, as well as issues related to sound production, which

Moore also argues is overlooked in analytical scholarship. By adapting Meyer’s premise and offering his own evidence for the shift between primary and secondary parameters, Moore provides a compelling case for syntactic form and syntactic climaxes (terms taken from Meyer

(1984, 46) but not explicitly used by Moore), where textures in rock generate hierarchical forms that do indeed provide climax and closure.14

The coordination of White and Quinn and Meyer is critical, as Meyer ultimately regards statistical exposure to music as the basis for musical style. And White and Quinn, with their model and use of the Billboard corpus, in turn provide empirical evidence that supports Meyer’s hypothesis about the increasingly syntactic nature of harmony based on a large collection of top-40 songs (n = 783) likely heard by most North American listeners ca.

1950–1995. Combined with Nobile’s theoretical framework, these studies illustrate that there

14 As I address in the next section, Moore’s assessment does align with perceptual research on form and auditory complexity. 21 are other communicative pressures at play in the stylistic development of popular music.

While it is appropriate to regard a three-state model of harmonic function as a stylistic influence on the development of common-practice music, its applicability to popular music seems less so given the evidence.

Surface-level Features and Perception

Each study above also highlights the relatively poor reliability of inferring structure from harmony alone via a listener’s perspective. That is, first, it may be the case that popular music as a style is much too diffuse to force harmonic function into a three-state model.

Second, studies on form theory and music perception suggest that other parameters such as rhythm, meter and form may provide the best frame of reference for musical organization and syntax.

William Caplin (2003) outlines three types of generic formal function: initiating, mediating, and cadential. Broadly speaking, Caplin employs these categories to indicate beginnings, middles, and ends of discrete formal units, as perceived by listeners. The perceptible characteristics of each type specify thematic development: presentational material aligns with initiating function and is generally characteristic (i.e., more theme-like), continuational material expresses mediating function and is less thematic, and cadential material is not thematic at all and is instead highly generic.

Rhythm and texture play a pronounced role in Caplin’s theory, as the language he uses to describe formal sectioning coordinates thematic (i.e., harmonic, but also melodic) and extra-thematic (e.g., rhythmic and textural) concerns. For example, in describing the four

22 essential features of continuation function, nearly all harmonic concerns are presented in tandem with easily perceptible changes in the musical surface: continuational sections demonstrate 1) phrase-structural fragmentation, 2) accelerated harmonic change, 3) increases in surface rhythmic activity, and 4) sequential harmonies.15 As such, Caplin’s balanced descriptions of the generic characteristics of small forms are a much more-accessible starting point to form and formal functions than concerns of harmonic prolongation and cadences alone.

The proof of the perceptual utility of surface-level features in formal segmentation, and rhythm in particular, comes from a study conducted by Lucy Pollard-Gott (1983) at

Princeton University. The study tests how musicians and non-musicians identified the components of musical structure by listening to Sonata in B-minor by Franz Liszt. The participants’ task was to “learn as much as possible about it [the sonata] through careful listening” (72) and “that they should make an active effort to understand the structure and properties of the piece.” (73) This process was divided into three parts: 1) listening and notetaking, 2) comparing passages on an 11-point scale, and 3) listening and notetaking again within a week of the first hearing, with the ability to hear passages multiple times.16 (Note only half of the participants were allowed multiple listenings on multiple days. The other group was only allowed to perform step 3 once in one session.) After this process, participants performed a classification test and an adjective rating task to evaluate their

15 Only the latter point is strictly harmonic, but by the nature of a sequence listeners can still attune to incremental changes in pitch height. 16 Pollard-Gott notes that “nonmusicians tended to discuss each passage in isolation, whereas musicians made comments which related one passage to another” (73). Perhaps this speaks to the modular nature of pop-rock form, that formal sections do not necessarily need to be harmonically related to be understood as components of the whole. 23 familiarity with the piece. For the classification test, participants were instructed to identify one of two themes and their variants using the letters A and B. In the adjective rating task, eight passages were played, and participants chose words that best described the character of the passage. These adjectives were bi-polar, meaning that words to describe one theme passage (e.g., Theme A: loud) were non-applicable to the other (e.g., Theme B: soft).

As might be expected, musician participants were more in-tune with the various dimensions of thematic identification such as harmony, melody, and rhythm. Non- musicians, on the other hand, relied on extra-thematic characteristics such as loudness, articulation, and general auditory complexity to identify and discern themes. Despite the facility of the musician population, however, it should be noted that thematic distinctions could only be made after repeated listening sessions. Similarly, only three “experts” (those who had performed or written an analysis of the sonata) were able to analyze the work on a primarily thematic basis—most musicians synthesized thematic and extra-thematic approaches.

Pollard-Gott’s results call into question harmony’s utility as a readily perceptible measure of musical structure: the majority of participants were Princeton performing musicians, who presumably have a high degree of statistical exposure to common-practice musics. Likewise, of the 50-person subject pool, approximately two-thirds were “experienced musicians” as determined by a four-question survey. The parameters for musical experience were also quite conservative—oriented toward those who primarily studied and performed common-practice music—as is clear in the survey’s questions, which required participants to report number of music courses taken, years of performing experience, years of piano

24 instruction, and maximum years of instruction on any instrument. (75) (The prioritization of piano performance is also curious, but perhaps sensible given that the piece in question was written for piano.) Regardless, the outcome of Pollard-Gott’s study suggests that harmony is not the most effective or efficient way listeners (either trained or untrained) realize musical structure. Instead, harmony is only truly accessible to those who are considered experts.17 So why do so many studies insist they are modelling a general perceptual process when they model harmonic function? Perhaps instead these studies model what a music theorist might hear, given a background in common practice music.

Multi-modal Function

So how should we (“we” meaning music theorists) approach style and musical structure if not by harmony? First, I do not believe we need to abandon harmony altogether as an assessment of style. Instead, I simply recommend considering the value of switching modalities to better understand the generational nature of popular music’s structures, including harmony, but also more salient and less syntactic features such as form, meter, texture and timbre. If harmony is acts as a perceptual symbol under Barsalou’s theory, then harmony as a stylistic component is potentially much more dynamic than scholars acknowledge. That is, a multi-modal approach affords a multi-dimensional take on music’s organization.

17 This tracks with the “mere-exposure effect” outlined by Zajonc (1968) and Huron (2006), which claims that increased exposure to a new stimulus increases one’s comfort with the stimulus. 25

Howard’s quote from chapter 1 again illustrates this, where her pursuit of characteristic sounds is incredibly dynamic. Yes of course, by her calling a chord “The James

Brown chord,” Howard likely refers to a particular orientation of intervals within a network of other harmonies. But it also clear that the “James Brown chord” is so much more than that—the chord is a social symbol that is categorical of style and a physical symbol that is categorical of performance. For Howard, she explicitly intertwines these facets of listening, performance, and creation. In opposition to strictly formalist approaches to harmony in popular music, the function of this chord is entirely dependent on its perceptual modality. And it is clear from Howard’s interview that its hierarchical position within a phrase is not a priority for her (this is what she means when she states “I don’t care about chords.”).

Instead, the primary function of the chord is to auditorily evoke James Brown to the listener

(and of course herself).

In music theory, notational symbols consistently act as perceptual symbols. When a student provides a Roman numeral for a chord or labels a formal zone, the ideal pedagogical goal is that the student demonstrates their understanding of the function of the musical object—its identity and syntax—through the symbol. With enough exposure to these symbols in a specific stylistic context, students then begin to approximate the characteristic compositional choices of a composer, which in turn reveals or reflects the rules and strategies of a historical period or genre. Moreover, by asking students to sing or perform harmonic progressions or articulate how an increase in surface rhythm signals a formal transition, concepts like harmonic and formal function become more concrete or perhaps even relevant to students by considering their performative aspects. This dissertation takes

26 the same approach to function but places the performative aspects of popular music first to develop a working theory of structural organization and style.

In subsequent chapters, I work from the following framework: I regard popular music artists as unique agents of musical communication in that they hold distinct but complementary roles as listeners, performers and composers. Because of this intersection, I assume popular music artists face a wide variety of pressures or constraints on how they develop and communicate musical information. These pressures sort broadly into the tonal- harmonic constraints of their instrument, the impact of stylistic influence and their personal experience and training as a musician. I start with the fretboard of the electric guitar to develop a model of guitar performance that takes into account an ecological theory of affordances, which suggests that performers generally prefer to maintain physical parsimony when developing musical surfaces. As I demonstrate, structures, such as formal structure, meanwhile arise when performers abandon affordances. I then apply this performance practice model to two digital collections of popular music songs, as well as real-time performances by local and semi-professional practicing pop-rock musicians. These observations help shape understanding of the rules and strategies (to use Meyer’s terminology) that perhaps influence the stylistic development of popular music.

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3. Chapter 3: Gesture as Function in Rock

In this chapter I conduct an interdisciplinary investigation of the role that fretted instruments and gesture play on harmonic and formal function in pop-rock music. I present five principles of instrumental performance in the context of theoretical, analytical, and empirical evidence to advocate that a performer-oriented approach to music analysis provides an intuitive and systematic method to model musical structure in rock. Application of this model in case studies and to a corpus of rock songs reveals that the surface of rock music is largely born of affordances—that is, songwriters and performers of this style consistently demonstrate the tendency to maintain parsimony in instrument space, lending weight to the theory that the physical aspects of music-making are a driving force behind harmonic and formal syntax. Gestures within this space therefore become a critical tool for understanding the generation of harmonic and formal function, as well as a means to explicate instances of ambiguity.

For example, a brief analysis of Paul McCartney’s navigation of instrument space in

“Hey Jude” disambiguates the harmonic concerns presented by de Clercq and Temperley

(2011, 57–58). Figure 3.1 summarizes that de Clercq hears the passage in B-flat, whereas

Temperley argues for the prolongation of F major. Gestures in the context of form meanwhile suggest that McCartney conceptualizes F as the structural dominant of a local B- flat tonal center, even as issues of style and tuning constrain his compositional-performative choices.

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Figure 3.1. de Clercq and Temperley’s analysis of “Hey Jude,” beginning of the bridge, under competing tonal centers.

The passage in question begins with a descending bass line on B-flat, creating a pronounced textural contrast from the previous verse. As the line progresses, McCartney quickly encounters a harmonic barrier—even though one might aurally expect an E-flat in a

B-flat tonal center, it is impossible for McCartney to play E-flat without shifting to a different position on the instrument. Doing so would violate the textural coherency of the descending pattern. McCartney is instead forced to play an E-natural as the lowest note the instrument affords, under the pressure of style and tuning. Having reached the lower-most boundary of instrument space, McCartney then redirects the line by arpeggiating the C-major chord around F.

Figure 3.2 illustrates how McCartney tonicizes F through a type of performative counterpoint. E-natural is traditionally understood a melodic step below F, and the following

G is a step above; however, by treating the fretboard as a topographical space and using the

Cartesian methodology introduced in De Souza 2018, the note C (third fret on the A string) is also analogous to a step, a performative step, due to its proportionate distance from F.

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Once centered on F, the following departing gesture reveals dominant function. Up until this point, McCartney navigates the fretboard parsimoniously. But as the next phrase begins

(“Don’t you know that it’s the fool…”), audio cues in the recording suggest that McCartney performs an audible slide up the E string. In doing so, F becomes marked as a place from which to depart, not unlike the role of the dominant in pitch space, and B-flat is treated as both a harmonic and physical destination.

Figure 3.2. Topographical distance in McCartney’s arpeggiation of the C major chord, physical centering around F, and functional shift to restart the phrase.

Through a close examination of McCartney’s transitions within fretboard space, I address the generated aspects of musical communication outlined in Chapter 1 by focusing on the execution of a musical surface from a songwriter’s perspective under an ecological theory of affordances. The songwriter is understood as an agent who, like the listener, is subject to pressures of stylistic convention. Because composing/performance is an acutely

30 embodied act (Zbikowski 2017, 33), the songwriter encounters a gamut of ecological affordances, including the constraints of the physical-harmonic makeup of their instrument, their experience, and their compositional preferences.

Affordances

At a most basic level, the theory of affordances is similar to statistical entropy—at any given point, all actions are possible, but some actions are more likely to be executed due to the characteristics of a given domain. One of the first domains considered by J.J. Gibson

(1966), the founder of the theory of affordances, was the environment as it acts on an animal. This initial treatment of affordances is largely based on the perceptible aspects of a physical domain. However, researchers have also studied the affordances of conceptual spaces and objects. For example, Kirsh (2013) found that dancers who performed mental simulations of their routines, as opposed to full-out physical practice, demonstrated enhanced memory, technique, and timing in subsequent performances. It is theorized that the dancers used the cognitive processes of projection (i.e., imagining their bodies in space) and anchoring (i.e., simulating the physical properties of their bodies) to embody how their performances would occur in a physical space (17, also see Cook 1990, 77). In music theory research, conceptual spaces are similarly designed to afford interpretations of musical works; examples include geometric pitch space (Tymoczko 2011), a “common network” of the key centers in the Minuet from Beethoven’s first symphony (Lewin 1987, 170), or musical form

(Cone 1968). Each has its own parameters that dictate boundaries and permit or afford movement (i.e., interpretations) within.

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For performers, instrument space is both physical and conceptual. As soon as a performer picks up an instrument, that instrument becomes part of their body schema (Kirsh

2013, 3; De Souza 2017, 54) and its physical and conceptual affordances are enacted. It is at this point where instrument space becomes an “enactive landscape” where the music produced is the result of “the set of possibilities that can in principle be brought into being when an agent [the musician] interacts with an underlying environment [the instrument] while engaged with a task or pursing a goal [playing a song]” (Kirsh 2013, 11). It is these considerations—the physical, conceptual, and the capabilities and preferences of the performer—that contribute to a modern definition of affordances and, in the case of music performance, determine what is eventually conveyed to the listener.

As observed in other studies, physical aspects of instrument affordances have been shown to have a pronounced impact on musical structure. For example, de Clercq and

Temperley (2011) imply that the guitar may be a generative force in pop-rock chord progressions; pointing to a pentatonic collection commonly observed in their corpus and stating that “open chord voicings [on guitar] may be preferred harmonic choices irrespective of the tonic of a particular song” (67). In an analysis of Bob Dylan’s “Queen Jane

Approximately,” De Souza (2017) presents a generalized model of harmonica performance to argue that drawing (i.e., breathing in) on a harmonica is over-determined in blues styles due to the wider range of “blue notes” (lowered scale degrees in a major context) available to the performer (68). White & Quinn (2017), studying key profiles in piano repertoire, find that keys with more accidentals were more likely to feature chromatic tones and modulate; that is, black-note key pieces modulate more frequently to white-note keys. The authors

32 suggest that this may be due to the tiered arrangement of the keyboard, where less effort is required to articulate white keys from black ones than vice versa (538). In the same vein, a study conducted by Huron and Berec (2009) measures the interaction of affordances in trumpet works and reports that many of the repertoire’s mainstays are composed in a manner that best facilitates idiomaticism; in other words, a work’s phrase length and key are optimal for breathing and fingering as affordant characteristics of trumpet performance.

Robert Gjerdingen (2009, 123–125), in response to Huron and Berec, advocates that a holistic definition of musical affordances is one that also considers social constraints (i.e., a musician’s experience and preferences) and style. De Souza echoes similar concerns about experience (2017, 51–83), who argues that performance is “negotiated” (63) by the performer’s ability or capacity to interact with the instrument. A performer’s understanding of style also shapes musical organization. Meyer (1989, 3–37) describes style as a replication of patterning as a result of human behavior. Thus, the patterns that composers employ are the result of a hierarchy of cultural and psychological constraints. Temperley (2004) treats style in a similar matter, where through a process called “communicative pressure” (330) the onus is placed on the composer, performer, or improviser to convey the structural features of music (e.g., the components of musical style) to the listener through the music’s surface.

Both Meyer and Temperley regard pitch and meter as primary to style, but also admit texture and timbre are also pertinent indicators even if they are not prioritized in their studies.

Gjerdingen and Perrott’s (2008) “radio dial” experiment clearly demonstrates the stylistic utility of these parameters, where listeners were able to identify musical genre in less than one second.

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As music is a temporal medium, tempo and the pace of surface rhythms are also critical affordant factors. Fitts’s law (Fitts 1954) prescribes that accuracy in physical performance is contingent on both speed and distance traversed. And though this relationship may be obvious, Fitts’s law has demonstrated a marked impact on both notated and performative aspects of musical structure. Specifically, studies by David Huron (2016,

80), David Temperley (2019), and Sundberg, Askenfelt & Fryden (1983) have independently observed that either composers of notated music or performers themselves have a tendency to employ longer note durations when approaching a large melodic leap: composers specifically use longer note values before leaps, whereas performers tend to employ rubato.

By convention, performers are therefore afforded “more room,” so to speak, to mentally and physically prepare for and execute difficult performative gestures.

Analysis: Affordances in “All Day and All of the Night”

In the case of fretboard performance, one of the central points of investigation of this study is to advocate that, due to stylistic convention of sustained musical texture and the general lack of rubato, the best place for a performer to enact a difficult physical transition is at a hypermetric or formal boundary (e.g., the repetition of a harmonic cycle or the change in formal section). That is, these important structural boundaries offer the performer the highest levels of physical affordance without violating the conventions of musical style.18

This practice is exemplified in the song “All Day and All of the Night” by The

Kinks. De Souza (2018) demonstrates how guitarist Dave Davies uses two separate

18 Pop-rock drummers often play the crash cymbal on the fourth hypermeasure of a harmonic cycle, perhaps masking the auditory result of a large shift in instrument space. 34 performative gestures to produce the song’s iconic power chord riff. Critically, these choices are form-dependent: “Dave Davies does use the cross-string (0, -1) interval for the F and Bb power chords at the beginning of the song’s bridge. But in the riff [in the introduction] he realizes the same chords through the along-string route” (13). By doing so, Davies distinguishes these formal sections through his navigation of fretboard space, even as the notes he plays are harmonically identical. De Souza also observes a gradual expansion of the fretboard space that culminates at the chorus. That is, in addition to employing two different fingering patterns, Davies also articulates the riff in distinct areas of the fretboard.

From the start of the song, Davies performs in the lower register near the headstock, first with the along-string gesture in the introduction, and then using the cross-string gesture at the start of the bridge. But as the bridge concludes, Davies traverses up the neck to A2

(fret 5, string 1) to approach D3 (f10, s1), the tonal center of the upcoming chorus.19 Here, the cross-string version of the riff repeats around A2 (A–G–C–A), further pushing the boundaries of the fretboard space. At the arrival on D3 (10, 1), the chorus again initiates the primary riff. Curiously, various performances show Davies playing both versions of the riff in this section, articulating the transition from C to F by along-string (8, 1) → (13, 1) and cross-string (8, 1) → (8, 2) fashion. In this way, the chorus synthesizes the reckless energy of the introduction with the conservatism demonstrated in the bridge.

As De Souza points out, the gradual ascent along the fretboard reinforces the song’s overall intensification toward the formal climax of the chorus (16). And while the internal transitions of the riff itself are noted earlier in De Souza’s analysis, as well as the transition

19 To treat the fretboard as a coordinate plane, my string labels are opposite of De Souza’s: (123456) or (EADGBE). 35 from the intro/verse to bridge to chorus, his analysis stops before the transition back to the verse. This, however, is a critical point in the form—the built-up energy formally, harmonically, physically, and ultimately functionally discharges via the leap from D (10, 1) to

F (1, 1).

Figure 3.3 models Davies’s navigation of fretboard space. Nodes on the fretboard visualization trace his performance, starting with chord 1 at fret-string coordinate (1, 1).

Each formal zone contains color-coordinated slurs to show transitions within the form: intro/verse 1 is pink, the bridge is blue, and the chorus is green. Gradient slurs indicate transitions from each zone. Thicker slurs indicate larger transitions within instrument space.

To supplement the figure, the following table also details each of Davies’s internal and cross- form transitions. As highlighted, most of Davies’s internal performative transitions are relatively conservative, even as the along-string patterns are assumed in verse 1 and chorus 1.

With the exception of the transition to the bridge (node 5 to node 6), the largest gestures in instrument space specifically coordinate with formal transitions.

With this evidence, the segmentation of musical form is an embodied process, where

Davies treats the harmonic-physical zones of the guitar fretboard as distinct from one another in respect to form and formal function. In terms of physical affordances, it would have been easier for Davies to perform the chorus material at D3 on the A string (5, 2) instead of transitioning up five frets on the E string to (10, 1). However, affordances of style and Fitts’s law potentially shape Davies’s rendition. Specifically, a stylistic hallmark of rock guitar performance is the open-fifth power-chord shape, which Davies employs throughout the song. By merit of featuring a thicker string, Davies seems to prefer to maintain a

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“thicker” texture by relegating most of the chords to the low E string. My own experiences playing rock guitar also lead me to understand that power chords played on the E string are more resonant than those sounded on the A string. Likewise, Davie’s choice to play the chords on the lowest string also mitigates the risk of striking the B string, whose added third would also violate the timbral- stylistic conventions of rock—an important concern given

Davies’s erratic and occasionally inaccurate playing (De Souza 2018, 13). Finally, the rhythmic values of the riff itself afford larger transitions through the use of a rest on the motif’s last beat. In this way, the rhythmic structure of the riff potentially models Davies’s need for more space to execute performative transitions, in accordance with Fitts’s law.

37 Intro/Verse 1 Fret 1 2 34 567 6: E 5: B 4: G 3: D 2: A 1: E 1 2 4 3 5

Bridge 1 Fret 1 2 34 567 6: E 5: B 4: G 3: D 2: A 6 10 1: E 7 5 8 9 11 Verse 2 Chorus 1 Fret 56789 10 11 12 13 6: E 5: B 4: G 3: D 2: A 1: E 1 11 13 12 14 15

Figure 3.3. Fretboard map of internal and cross-formal transitions in Dave Davies’s performance of “All the Day and All of the Night” by The Kinks.

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Formal zone Chord number Slur color Gesture type Distance Intro, Verse 1 1, 2, 3, 4, 5 pink internal 3 5, 6 pink to blue transition to Bridge 1 2.24 Bridge 1 6, 7, 8, 9, 10, 11 blue internal 2.5 11, 12 blue to green transition to Chorus 1 5 Chorus 1 12, 13, 14, 15 green internal 3 15, 1 green to pink transition to Verse 2 9

Gibson (1966, 134) describes affordances simply: “affordances of the environment

are what it offers to the animal, good or ill.” But as performers know, the relationship

between the musician and instrument is not a one-way process—just as much as performers

interact with their instruments, instruments also interact with the performer by enabling and

sometimes constraining their creative process. Societal pressures likewise contribute to

musical development by measures of experience and style. De Souza (2017) aptly

encapsulates these facets of affordances when evoking the experience of “flow,”

characterizing the state as the optimized interaction of “over-learned patterns of idiomatic

performance” and consciousness (80). In songwriting, physical and cognitive domains are

similarly linked as the songwriter crafts the structure of their work from their instrument

while drawing upon their musical experiences.

Five principles of rock guitar performance

If function of a musical event such as a chord is defined by its action, identity, and

syntax, as it has historically been treated in harmonic measures of musical structure, then it is

by a small conceptual leap that function can also be defined by what choices songwriters

39 make while navigating instrument space, in the context of musical form and under the influence of physical and social constraints.

In line with the previously introduced performative concerns, the following analyses will highlight five principles of pop-rock music as they relate to fretboard performance:

1. Parsimony: Performers generally prefer to move as little as possible within instrument space. Open strings facilitate fretboard parsimony by mediating performative distances.

2. Harmony: Characteristic harmonic progressions are often a byproduct of maximizing performance affordances.

3. Form: Formal function and type can be defined by characteristic gestures within formal and instrumental boundaries.

4. Transitions: Formal boundaries are primarily articulated by larger transitions in instrument space. Larger inter-formal transitions can convey rhetorical or harmonic function.

5. Ambiguity: Gestures in instrument space can be used explicate instances of functional ambiguity. Performer preference for parsimony can create instances of harmonic ambiguity, such as non-tertian chords. Instances of melodic-harmonic divorce often arise when there is a conflict between what is idiomatic for the voice and what is idiomatic for an instrument, resulting in competing tonal systems.

Dave Davies’s performance of “All Day and All of the Night” exemplifies the first four principles. Specifically, Davies employs contrasting gestural patterns to articulate the same harmonic progression depending on the formal module (Form), generally moves as little as possible within each module (Parsimony and Harmony), and articulates transitions from one module to another with increasingly pronounced gestures in fretboard space, culminating in the largest transition as the harmonic cycle repeats (Transition).

By the principles outlined above, gesture acts as a primary measure of function in pop-rock. Performers understand harmonies as gestures in instrument space and formal

40 zones are similarly realized as harmonic patterns executed by a sequence of gestures. In this way, gesture is functional, in that gesture is an action-object in musical space that expresses its own identity (distance) and syntax (context within other gestures, harmonies, or form).

Most critically, like standing definitions of harmonic and formal function, the following analyses show that gesture is also a reliable measure of musical structure in rock. I explore and clarify this potentially radical conception of function and structure through a continuing series of case studies of pop-rock songs as contextualized by other music-theoretic analytical methods and through a corpus study of modal-pentatonic rock songs introduced in

Biamonte (2010).

A Cartesian Model of Guitar Performance

Modeling a performer’s interaction fretboard space requires careful consideration of the unique tonal and topographical features of the six-string guitar. These include differences in pitch mapping between the horizontal and vertical vectors of the fretboard and issues of pitch recursion due to string tuning—factors previously detailed in Koozin (2011) and De

Souza (2018) and summarized here. Not examined by these studies, but also considered at length here is the role that open strings play in facilitating performative transitions.

The task of measuring the impact of gesture on harmony and form is more complicated than simply tracking pitch distance in traditional notation. For example, in keyboard space traditional notation can act as an effective proxy for performative distance due to the nearly one-to-one mapping of individual keys to notated pitch.20 That is, as a

20 Chromaticism disrupts this relationship slightly. For example, B-flat occupies the same space on the staff as B-natural. However, a general linear trajectory is still maintained. 41 performer moves horizontally to the right (“up”) on the keyboard, pitches on the staff ascend by step in pitch space. Pitch height and notational pitch space therefore demonstrate a dependent relationship under a generalized horizontal model of keyboard performance. A guitar’s fretboard space shares a similar mapping of pitch distance and physical distance for its horizontal (i.e., along-string) vector, but this parallelism is disrupted by the vertical (i.e., cross-string) vector which, depending on the guitar’s tuning, typically traverses pitch space by perfect fourth instead of chromatic step.

Issues of tuning also result in a recursive fretboard-pitch space. Assuming that the guitar is in standard tuning (EADGBE), as a guitarist moves up the fretboard (toward the body) and passes the fifth fret, they are afforded an additional place to play the same note.

For example, the note D3 can be played as an open string, on the fifth fret of the A string, or on the tenth fret on the E string. In this way, notes in fretboard space does not share a direct mapping to traditional notation because, unlike a keyboard, the same note can be articulated in different physical positions on the instrument. Similarly, a vertical “step” (i.e., crossing a string) does not correspond to a diatonic or chromatic step in pitch space. It is for these reasons that distance in pitch space is not a reliable measure of performative distance in guitar-driven works.

The model presented here is meant to approximate performance practice in real time. That is, it acts as a direct representation of the instrument’s fretboard. As such, the model is perhaps less generalizable than the one De Souza presents, and likewise gives less priority to relative chord shapes as described by Koozin. However, what the model loses in

42 generalizability it gains in its ability to capture the inherent constraints and performative preferences of pop-rock songwriters.

Like De Souza (2018), I rely on fret and string vectors (f and s) to track performative distance using the Cartesian formula. However, frets are necessarily treated as a finite set, from an open string (f = 0) to the highest fret on the hypothetical fretboard (in most cases,

24 frets, f = 24). I also depart from De Souza by ordering strings from 1–6 according to pitch height (lowest to highest, E–A–D–G–B–E), which are implicitly ordered in the set

⟨123456⟩.21 Doing so departs from pedagogical practice, but allows the fretboard to be treated as a coordinate plane by which to measure distance as it (sometimes) corresponds with pitch height.

Chords are represented by fret number under implicit string order. Shown in Figure

3.4, the pitch C3, played on the 3rd fret of the A string, coincides with De Souza’s fret-string pair (3, 2). The same pitch played on the low E string would contrastingly be represented as

(8, 1). Similarly, by building chords off of these pitches, a three-note C7 chord consisting of the pitches C–E–Bb is represented in set form as ⟨-323--⟩ if played on the A string, while same chord built from lowest E string would be ⟨878---⟩. Both fret-string and set representations of pitches will be essential for measuring performative distance with the

Cartesian formula.

21 De Souza labels strings in reverse: (654321) or (EADGBE). 43

Figure 3.4. Two voicings of a three-note C7 chord in fretboard space.

Function of Open Strings

Open strings create theoretical and mathematical complications in modeling guitar performance. In many respects, an open string can be thought of as an elusive fret—a note that exists just outside the boundary of the first fret. This follows Koozin’s methodology

(2011), where all chord shapes are treated as barred. For example, in voicing a G major chord, Koozin would use fret-interval type ⟨431114⟩ to represent the chord while projecting an imaginary barrier or barre before the open strings. As a result, each integer of the original tablature chord shape ⟨320003⟩ is increased by one. This method works well for Koozin because he is interested in the relative transitions and transformations of chord shapes. For our purposes, however, open strings are a critical component to fretboard affordances, as they often support harmonic and physical transitions. Moreover, in performance practice an open string does not exist out of the boundaries of the fretboard, but rather encompasses the entire horizontal vector of the performance space, thus creating an avenue for performers to articulate adjacent fretted notes with ease.

This tendency is observed explicitly in riff-based rock songs such as “Crazy On You” by Heart (Dreamboat Annie, 1976) and “I Believe in a Thing Called Love” by The Darkness

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(Permission to Land, 2003). Transcribed and notated in tablature in Figure 3.5, the primary riff of “Crazy On You” as composed by Nancy Wilson features a mix of open-string and fretted notes. Here the open strings serve two functions: harmonically, as an anchor for the song’s tonality and, performatively, as a means to transition from one sonority to another. Both uses are consistently encountered in pop-rock guitar performance, but present practical and mathematical obstacles when tracking performative distance through the use of the Cartesian formula.

Applying the Cartesian formula to measure the distance of between D3 (0, 3) and C3

(3, 2) results in an interval (i) of 3.162. That is, the formula reports that Wilson needs to move her hand or fingers the equivalent distance of (slightly more than) three frets to perform this note transition. This, however, clearly does not reflect practice, as Wilson shifts down one string and shift slightly to the right. She traverses only a very small physical distance, approximately the equivalent of one fret. The disconnect between mathematics, modeling, and practice is largely the fault of a coordinate-plane approach: open strings are treated as a fixed point to the left of the first fret, and so the Cartesian model tracks the distance from this leftward position to the third fret. An efficient solution to this problem is to instead conceptualize open strings an open horizontal vector where every fret is articulated at once. In doing so, the fret coordinate of the previous note, E3 (2, 3) is superimposed on the D string to better model performance practice.

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Figure 3.5. Transcription of main riff in “Crazy On You” by Heart, composed/performed by Nancy Wilson.

The fret position of D3 is replaced with an underlined integer (2, 2) to indicate it has been substituted from the previous note. Reapplying the Cartesian formula results in a much more agreeable 1.4 frets. As for the first note of the riff, the same practice applies, but in reverse: the following note’s fret coordinate (2, 3) is imposed on the first’s (0, 2), resulting in the substituted fret-string coordinate (2, 2) and a distance of 1. This models how Wilson would need to cross strings but not move her left hand to initiate the riff.22 The process of fret substitution is demonstrated in Figure 3.6 on the open strings of the riff, as indicated by asterisks.

22 Note this practice works best for monophonic lines such as this single-note riff. For chords, the same is applied to the lowest note of each sonority to approximate hand centering. If the lowest note of a chord is an open string, the fret position of the next-highest fretted note in the chord is imposed onto the lowest string. 46

**********

* an open string substituted with previous fret position

Figure 3.6. Open strings substitution of previous note’s fret position to better-model performative distance in “Crazy On You” riff.

Another function of open strings is to expand an embodied performative center. In the harmonic progression | I–V4/3–V6/5–I | contrapuntal bass motion prolongs the initiating and concluding harmonies. Specifically, the dominant chords are prolongational because the tones within depart and approach the tonic chords using parsimonious voice leading in pitch space—each tone in the dominant is resolved back to a tonic scale degree by step or by maintaining a common tone. The same principles of prolongation applies to guitar-driven rock songs, but with consideration to the physical domain.

Figure 3.7 presents a transcription and harmonic reduction of the primary riff of “I

Believe in a Thing Called Love” by The Darkness. Assuming a local tonic of F# minor, and a harmonic rhythm of mostly whole and half notes, the riff’s harmonic progression | i–III | iv |VII iv | III–(VII6)–III | i | resists paradigmatic categorization. While most chords can be reasonably labeled as either tonic (i, III) or predominant (iv, VII) by tonal or modal measures (Biamonte 2010), extrapolating dominant function requires some analytical hoop- jumping— either by arguing that 1) the final E projects a subtonic harmony in the span of

47 the eighth note, or 2) the C#–E dyad implies the minor dominant.23 An alternative approach would be to reduce the riff to harmonies occurring on downbeats.24 If these are deemed as the most structural, a transition around the circle of fifths (F#–B–E–A) is observed.

However, reducing the riff to downbeat harmonies discounts tonal root motion by ascending second (mm. 1–2) and ascending fifth (m. 3), which evoke rock’s stylistic root motion (Stephenson 2002).

F#m: iIII iv VII iv III VII 6 III i

Figure 3.7. Transcription and harmonic reduction of main riff in “I Believe in a Thing Called Love” by The Darkness, composed and performed by Dan Hawkins.

Clearly modal forces are at play, but regardless of tonal lens, a harmonic perspective does not convincingly reveal how these chords function within the context of F# minor.

From a performance perspective, however, the riff is quite intuitive—in fact, to play it requires no shifting whatsoever. As demonstrated in Figure 3.8, the hand stays centered around the second fret. By applying the Cartesian distance model and substituting open

23 Biamonte’s model also allows for the mediant chord to express dominant function in major contexts. 24 This follows Temperley’s (2004) methodology in determining the structural status of the cadential IV chord. 48

strings as detailed above, the parsimonious nature of the riff emerges. If the open strings A

and E are conceptualized as creating access to every fret at once (demonstrated by the

greyed string vector), every note in the riff acts a performative “step” away from the tonic

F#. Weak-beat harmonic transitions, especially those articulated by open strings, are

therefore largely be treated as passing sonorities due to affordances, thus giving way to the

more “structural” progression observed earlier (i.e., F#–B–E–A). Most importantly, the riff

as a whole is understood as an analogous to a tonic expansion due to instrumental stepwise

motion around a harmonic-performative center at F# on the second fret.

Fret 1 2 34 567 89 6: E 5: B String 4: G 3: D 2: A A B C# 1: E E F# G#

Figure 3.8. Pitch/fret proximity in the primary riff of “I Believe in a Thing Called Love” by The Darkness, composed and performed by Dan Hawkins. The hand is centered on F#.

The formal cycle (verse 1, verse 2, prechorus, chorus) of “I Believe in a Thing Called

Love” also evokes many of the same performance principles outlined earlier. Gestures

likewise shed light on ambiguous facets of its harmonic organization. Figure 3.9’s video

analysis illustrates that each formal zone expands fretboard space in contrasting ways.

Tonally, the verses evoke F# minor (aeolian), while the chorus features a modulation to E 49 major (mixolydian) via the structural dominant that concludes the prechorus. As with other examples, each module distinguishes its own fretboard space, which are outlined by the colored “mists” in the video (verses in blue, prechorus in pink, and chorus in green). During the second rotation through the form, similarly colored nodes mark the root of each chord, while slurs demonstrate transitions from one chord to the next.

The video ends with a network of roots positioned in fretboard space and linked by slurs. There, two prominent gestures are outlined. First is the large transition from d to the start of c, which again can be conceptualized as dominant (B) to tonic (E) in E major

(mixolydian). The second reinitiates the entire formal cycle from c to s, but the functional relationship between its chords (D to F#) is ambiguous. Scale-degrees in either tonal center

(6 to 1 in F# minor or 7 to 2 in E major) provides little support for a harmonic functional interpretation. However, it is likely that Hawkins still understands this transition as functional, as it features a larger gesture (identity) at the end of a formal cycle (syntax).

Figure 3.9. Video analysis of form and gesture in “I Believe in a Thing Called Love.” (Click icon above to view on my personal website. Video will be first on the page.)

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Instrument Distinction in Functional Analysis

Commonalities between voice-leading practices for keyboard instruments and the human voice suggests that stepwise motion is maximally affordant.25 Yet, in pop-rock music, instrumental parts consistently violate common-practice voice leading. Biamonte (2010) articulates these concerns while remarking on compositional practice and analytical methodology employed in pop-rock studies:

…in many vernacular genres—including blues, jazz, and rock—nontriadic tones are not unstable… common-practice rules of voice-leading and dissonance do not necessarily apply. The relative tension and stability of scale degrees and chord structures in a given song are defined by their immediate harmonic and melodic context against a background of broader stylistic conventions (95).

Schenkerian paradigms of linear motion are potentially powerful explicators of melody, but presume a concern for voice-leading and counterpoint often absent from the harmony layer, especially when it is iterated by rhythm guitar rather than keyboard (96, fn. 8).

Here, Biamonte observes that Everett (2009) perhaps gives too much structural weight to melodic tones, which are in turn not always harmonically supported by the guitar texture.

Furthermore, by arguing that non-tertian harmonies are not necessarily non-structural (in that they have the capacity to support melodic tones), she establishes the premise of her study: that pop-rock analysis should not always be couched in an Ionian-oriented perspective on harmonic function.

Biamonte’s study articulates the surface-level stylistic features of rock that analysts inevitably encounter, including non-tertian harmonies, a disconnect between melody and

25 Karpinski (2000, 148) suggests using the major scale as a point of pedagogical departure when introducing college students to aural training. When presented with an ambiguous pitch, students are similarly encouraged to sing down to a point of rest by step to determine its identity.

51 accompaniment, and pentatonicism. These are obstacles are attributed to guitar performance practice, such as the distinct lack of thirds in guitar textures due to dissonances introduced by the harmonic series through the use of distortion (97, fn. 16). Like many other analysts,

Biamonte sidesteps these issues by using pitch-class space to focus on schematic root- motion patterns. In doing so, she considers the pitch content of a guitar’s texture considered alongside that of the melody. However, pitch class reduction can only take an analyst so far.

For example, if a chord consists of stacked fourths, how would this non-tertian harmony be conveyed by a chord symbol or Roman numeral? Neither has the capacity to contextualize harmonic content without designating a chord root, and Roman numerals necessarily require a tonal center to frame scale degrees.

Pitch-class space is an incredibly effective system for understanding the harmonic- functional tendencies of vocal melodies and keyboard parts. With the understanding that the pitch content of a sonority within the context of a key is an indicator of functional category, harmonic progressions also reveal compositional paradigms implemented by the tonal framework of common practice-period works. But with pop-rock music, harmonic syntax is not as nearly as systematic, as demonstrated by Biamonte’s advocacy for modal function. A recent study by White and Quinn (2018) also reveals that pop-rock harmony, on the basis of chord syntax in the McGill-Billboard corpus, demonstrates eight functional states as opposed to the three one might expect in common practice music. Shown in Figure 3.10, the states are critically style-dependent: minor-mode songs and songs that employ jazz harmonies are relegated to their own functional circuit. White and Quinn’s study reveals that there are simply more harmonic-functional paradigms at play in the realm of pop-rock music. One

52 implication of this is that songwriters may be less constrained by harmony as a stylistic norm.

This, in tandem with the notion that pop-rock voice leading is not that of common-practice music, demonstrates the need for a closer look at the musical surface of pop-rock.

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Figure 3.10. The eight harmonic states of the McGill-Billboard corpus divided by style: a primary (T, S), minor mode (P, Q) and jazz (W, X) circuit. From White and Quinn 2018.

54 Stylistic Features of Modal Rock Songs

A central claim of this study is that the harmonic and formal paradigms of pop-rock music are largely a byproduct of the songwriter’s preference to move as little as possible in instrument space. Larger gestures are effective signals of hypermetric or formal transitions due to stylistic pressures for textural contrast after the structural repetition of a phrase. Up until this point, this claim has simply been a theory—a theory supported by four analyses.

But studies of style are at their best and most convincing when backed by a comprehensive examination of representative works. We readily see this in studies of form and harmonic- formal function, both in common practice (Caplin 2003; Hepokoski & Darcy 2006) and pop-rock repertoires (de Clercq & Temperley 2011; Summach 2012; Burgoyne 2011). In each, the authors undertake a systematic analysis of the components of musical style to reveal compositional paradigms employed a wide range of composers. Here I adapt this empirical methodology to do the same.

Biamonte Modal-Pentatonic Corpus

Without constraints on scope, empirical studies on the components of musical style effectively lose explanatory power (Gjerdingen 2014, 200–202). Hepokoski & Darcy and

Caplin, for example, focus their theories of formal function to 18th century works as composed primarily by Haydn, Mozart, and Beethoven. In doing so, the authors establish a well-regarded and practical theory of compositional norms for common-practice music by limiting their scope to the compositional practice of artists who are exemplars of formal paradigms.

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My own experiences performing in rock ensembles and the fourth-based and recursive nature of the electric guitar suggest that songs that use modal and/or pentatonic harmonic systems are where the instrument-based principles of parsimony best apply in popular music. The focus of the following empirical investigation will be on the songs listed in-text in Nicole Biamonte’s 2010 Music Theory Spectrum article “Triadic Modal and Pentatonic

Patterns in Rock Music.” These songs, comprising Anglophone rock tracks released between the late 1960s and early 1990s, provide the historical and stylistic focus necessary to provide a ground-truth measure of the relationship between gesture and harmonic-formal function in this repertoire.

Much of the following discussion is based on an exploratory approach to the corpus.

However, I do offer a statistical assessment of the predictive power of gesture on form near the end of the chapter. Performative, harmonic, and formal data from the Biamonte Modal-

Pentatonic corpus will instead be used to corroborate (and occasionally question) current understanding of the stylistic and functional components of rock music.

Materials and Method

Spanning from the year 1966 to 1991, the corpus contains 60 full-score (i.e., non- reductive, with surface-level pitches and rhythms) song transcriptions in both tablature and traditional staff notation. Each song was retrieved in Guitar Pro format from the website ultimate-guitar.com, a popular resource for those looking to learn how to play pop-rock songs.

The final corpus of 60 songs was curated from the 71 songs originally listed in Biamonte’s article according to the following criteria. Each song’s transcription had to:

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1. be listed in “Triadic Modal and Pentatonic Patterns in Rock Music”

2. be rated four stars or higher by the ultimate-guitar.com community

3. contain at least one rhythm guitar track and not be piano-driven

4. be free from obvious performative, rhythmic, formal or harmonic errors

Two songs did not meet the necessary threshold for community-rated quality. Six were discarded due to notational errors such as inaccurate rhythms and pitches or incorrect formal progressions due to misplaced repeats. Two were excluded by the merit of being piano-driven. Finally, one song was accurate in rhythm and pitch but the tablature did not reflect the performance practice of the artist (there were many obvious fingering incongruities) and was thus also excluded. This process of elimination resulted in 60 songs and 70 rhythm guitar tracks for analysis, shown in Appendix A. Solo passages were not included in this study.

Songs were first downloaded in Guitar Pro under the conditions outlined above.

Like other notational software such as Sibelius or Finale, Guitar Pro allows users to notate multiple instrumental and vocal parts simultaneously, which are entered and played back in both traditional and tablature notation. An advantage of using Guitar Pro is that the program exports individual instruments (“tracks”) in a variety of notational formats. Exporting tablature as a text file, in particular, produces a systematically organized ASCII document from which rhythm, meter, and pitch can be inferred.

Pitches in pitch space are realized by coordinating string tuning (encoded as metadata in each track) with fret number. All transcribed pitches are also set in a rhythmic and metric framework by their position within the notated barlines. These barlines,

57 represented as vertical bars (“|”), act as containers for fret numbers and dashes (“-”).

Dashes serve as a way for the performer to approximate the relative position of notes, but the quantity of dashes in a measure also indicates the measure’s smallest rhythmic value. For example, four quarter notes in a single measure of common time would contain eight dashes: four as two-dash buffers for every barline (“| - - “ and “- - |”) and one following each of the four fret numbers (“4 - 5 - 6 - 7 -“). When rhythmic values are mixed, the aggregate number of dashes is increased; as an example, four eighth notes and a half note are represented as

| - - 5 - 5 - 5 - 5 - 6 ------|

Here each “5 -” is an eighth note and “6 ------” is the half note. Again, the first and last two dashes serve as buffers and do not contribute to the rhythmic and metric organization of the measure. Notice how there are four pairs of characters in the half note, indicating how the measure’s smallest note value subdivides the larger ones. This innate systematization facilitates computational processing using a script called gptab2str (“Guitar Pro tab to string”), written by Craig Sapp specifically for this project to process ASCII text and convert into

Humdrum notation (Huron 1995). This conversion process is illustrated in Figure 3.11.

58

Humdrum conversion Guitar Pro with form annotations

ASCII export

Figure 3.11. Tablature formats, “Crazy Little Thing Called Love” by Queen, verse.

59

Once each ASCII tab is converted to Humdrum format, the vertical orientation of the strings allows for a straightforward analysis of string and fret coordinates. Each column represents one string of the guitar (tuning information is encoded as metadata from the original Guitar Pro file), while each row designates either a fret (any integer) or a rest (a dash converted to a period).

By calculating note-to-note distances in fretboard space, I aim to approximate how a performer moves their left hand within the space of the fretboard. To do so, I extract the lowest note of every chord in the musical texture.26 From here, open strings are treated as described earlier: when the lowest note is an open string, its fret position is replaced with that of the previous note. If there is no previous note, such as at the beginning of the song, the following note’s fret coordinate is assumed instead. This encoding process produces a representative model of the performer’s orientation in fretboard space. All that is left is to coordinate gesture with other compositional features such as form.

Despite the notational specificity the tablature provides, formal information encoded in the original Guitar Pro files does not carry over to the exported ASCII files. Many of the user-encoded formal labels were also often inaccurate, inconsistent, and/or commonly conflated formal modules of a similar function. In response, the formal module type and segmentation of each song was determined and encoded by hand using the following methods.

26 This method of note-to-note analysis has also been described as “salami slicing” by Quinn (2010) and later by White (2013, 127). The term refers to the thin “slices” of data produced when each verticality of a musical texture is catalogued. White regards them as analogous to figured bass-notation (ibid.). This is also how they are treated here: each slice represents an instant in the performer’s embodied experience while also conveying relevant fret, pitch, and rhythmic information. 60

For formal analysis, this study largely follows the methodology outlined in de Clercq and Temperley (2011) by using two analysts to cross-validate interpretive decisions.

Specifically, I (NS) and Daniel Shanahan (DS) conducted a formal analysis of each song independently and then met to resolve any analytical differences. We agreed from the outset to be intentionally generic in our assessment of musical form and approach formal segmentation from the perspective of a general listener. For example, we did classify extended (non-solo) instrumental breaks as “interludes” but did not distinguish between subsequent iterations (e.g., “interlude A” vs. “interlude C”) even if they were contrasting. In doing so, we aimed to model the more generic characteristics of musical form in rock as outlined by Summach (2012). Overall, we agreed on the general formal zones of each of the

60 songs at a rate of 90 percent. Seven songs, each of which contained less conventional structures as outlined below, required revisiting and discussion.

Our contrasting interpretations largely came down to differences in hierarchal hearing, even as the zone’s label effectively conveyed the same function. For example, in

“Crazy Little Thing Called Love” by Queen, DS hears the first formal module (mm. 5–16) as a self-contained verse. NS, on the other hand, hears DS’s verse as segmented into a strophe

(mm. 5–13) and refrain (mm. 14–17). Both verses and strophes are functionally similar in that they serve to further the narrative of the song toward its goal (Summach 2012, 110); however, DS’s interpretation has the merit of being more generic and thus more accessible to a general listener (our goal from the outset), while NS’s demonstrates a sensitivity to textual recursion at the sacrifice of creating a three-measure formal segment.27 One song,

27 By labelling the refrain as a perceptible formal unit, I depart from Summach’s conception of a strophe as a standalone module. However, in the following analyses both “strophe” and “refrain” segments are categorized 61

“Lola” by The Kinks, presented significant analytical obstacles to both analysts due to a variety of factors, including the song’s frequent reprise (“Lo-la, L-O-L-A, lo-la…”) and general textural intensification toward the fourth module (“Well I’m not the world’s most passionate guy…”) which features the energy of a chorus but shares the same melodic and harmonic structure as the first module (presumably a verse). In response, we elected to use an srdc formal scheme comprising statement-restatement/response-departure-conclusion

(Everett 2009) with an interpolated bridge, as we believe these labels to be a generic but appropriate approach to the song’s large-scale formal organization.

Once reconciled between the analysts, the initiating measures of each formal zone were marked in correspondence to the Guitar Pro transcription. Labels for the formal sections were then inserted into the corresponding Humdrum file at the indicated measure.

With evaluations of performative distance and formal organization in place, various analyses were conducted to investigate the first four performance principles outlined earlier.

Harmony: The Surface of Rock Music

Music theorists have generalized about the compositional paradigms and schemata that underpin rock’s organization. For example, Stephenson (2002) argues that chord root motion in rock music largely moves by ascending fifth, ascending third, and descending second (102). Common-practice music, on the other hand, mostly features root motion by

more generally as primary formal modules. Since the goal of this paper is to model embodied performance practice, and the presentation of a refrain often starts with a notable change in texture, this segmentation allows us to investigate performative similarities between strophes and verses, as well as refrains and verses, on the basis of text (in)variance. 62 descending fifth, descending third, and ascending seconds (103).28 A key advantage of the

Modal-Pentatonic corpus is that it allows what I believe to be the first close examination of the surface-level features of rock music using empirical methodology.29 Its note-to-note approach supports current understanding of the structural components of rock through consideration of surface-level musical features such as pitch and rhythm in the context of performative considerations. Stephenson (2002) therefore acts as a critical source of investigation, for he makes explicit claims about non-reductive pitch space which can be tested empirically through the Modal-Pentatonic corpus.

Figure 3.12 provides the frequency distributions of note-to-note pitch transitions in the Modal-Pentatonic corpus in pitch class space, under inversional symmetry (e.g., fourths and fifths, seconds and sevenths, etc. are treated as equivalent). Figures 3.13 and 3.14 meanwhile report the same in directional pitch space, modulo 12. These values are calculated from the lowest note of each verticality in the guitar texture, under the assumption that the majority of sonorities in rock music are in root position.30 To be clear, however, I do not claim that the following data consists strictly of root-motion transitions. For example, an arpeggiated chord each note transition would be included even though one note (presumably the first one)

28 There is room for expansion of Stephenson’s claims about root motion, however, as he does admit rock also frequently uses common-practice progressions, especially in cited songs written in the 1950s and 60s (e.g., “Peggy Sue Got Married” by Buddy Holly, p. 106). He also concedes that progression and retrogression is an important distinction between rock and common-practice harmony (105), though this feature of rock harmony is not treated here. 29 Some may argue that White and Quinn (2018) and de Clerq and Temperley (2011) provide such a surface- level assessment. I disagree, specifically because they use pitch-class-based chord symbols or Roman numerals to relate harmonies in pitch-class space. As I argue earlier, much is lost through harmonic reduction, including directional motion in pitch space and rhythm. 30 de Clercq and Temperley (2011) report that 94.1% of chords in the Rolling Stone 200 corpus are in root position. Similarly, a parsing of the McGill-Billboard corpus reveals that 91% of its chords are root position.

63 would actually act as the root of the chord. Instead, these bass-note melodic intervals reflect the aggregate pitch transitions that a guitarist and, to a lesser degree, a listener encounter as they move through the song. In this way, my approach is purely syntactic (i.e., note-to-note) and also considers changes in texture due to shifts in pitch height.

64

Figure 3.12. Frequency of inversionally equivalent bass pitch transitions in the Modal-Pentatonic corpus.

65

Figure 3.13. Frequency of directional bass-pitch transitions in the Modal-Pentatonic corpus.

66

Ascending 1 2 3 4 5 6 7 8 9 10 11 Total instances 843 2912 1735 738 1329 85 1150 238 211 258 45 9544 proportion 0.09 0.31 0.18 0.08 0.14 0.01 0.12 0.02 0.02 0.03 0.00 Descending -1 -2 -3 -4 -5 -6 -7 -8 -9 -10 -11 Total instances 789 2332 1317 605 1166 120 1151 263 437 672 148 9000 proportion 0.09 0.26 0.15 0.07 0.13 0.01 0.13 0.03 0.05 0.07 0.02

Figure 3.14. Frequency of directional bass pitch transitions in Modal-Pentatonic corpus.

67

Overall, the texture of the Modal-Pentatonic corpus consists primarily of pitch motion by major second, minor third, and perfect fourth (n = 18,544 note transitions). Excitingly, many of Biamonte’s harmonic structures are realized through these results: the Aeolian progression consists of root motion by step and the double plagal progression is categorized as a series of descending fifths or ascending fourths. On the other hand, Stephenson’s theory of root motion is potentially refuted. There are proportionally more ascending seconds (n =

2912, 15.7%) than descending seconds (n = 2332, 12.5%) and pitch motion occurs more often by ascending fourth (or descending fifth) (n = 1329, 7.5%) than descending fourth (n

= 1166, 6.3%). Curiously, the rate of ascending (n = 1150) and descending (n = 1151) fifths is nearly equivalent at a rate of 6.2% each.31 Much of this data is similar to those reported in de Clercq and Temperley’s study of the relative motion of chord roots in the Rolling Stone 200 corpus.

Given that our study views movement by perfect fourth and major second as most intuitive to a guitarist, based on frequency alone it seems that harmonic choices based on these transitions are most affordant in practice. The prevalence of ascending minor thirds also supports Biamonte’s pentatonic perspective of the tonality of rock music, at least on rock’s musical surface. However, why these notes are executed so frequently in performance is less clear immediately by the proposed theory of affordances.

Taking a closer look at representative songs, fingering and relative hand position seem to be at play. Specifically, the directional tendencies of minor thirds depend on the

31 Calculations of bass-pitch motion were made first in directional pitch space, then reduced to modulo twelve, thus the potential disjunction between inversional distances.

68 physical-tonal centering of the index or smallest finger in fretboard space. For example, to play the introduction of “Radar Love” by Golden Earring (transcribed in Figure 3.15), one would place their smallest finger on the fourth fret. Doing so positions the performer to articulate the minor third from C# (4, 2) to E (2, 3) without shifting. The same is true for the following minor third from F# (4, 3) to A (2, 4) later in the riff. Contrastingly, the articulation of a descending minor third is dependent on the centering of the index finger.

As shown in Figure 3.16, in the lead-up to the refrain of “Everybody’s Got Something To

Hide (Except for Me and My Monkey)” by The Beatles, playing D-natural (5, 2) with the index finger allows for the following B-natural (7, 1) to also be executed without shifting.32

Finally, many of the ascending and descending minor thirds are simply a byproduct of open strings, as shown in the guitar parts of “Break on Through” and “Love Me Two Times” by

The Doors (Figures 3.17 and 3.18). By these observations, it may be the case that minor thirds are over-determined in rock music due to the innate affordances of open strings, the physical tendencies of the human hand and the prevalence of pentatonic structures.

32 This affordance is also extended to the power-chord shape (open fifths), though less convincingly because the added fifth in the following chord necessitates a shift in the vertical vector.

69

Figure 3.15. Ascending minor thirds in “Radar Love” by Golden Earring.

Figure 3.16. Descending minor thirds, “Everybody’s Got Something to Hide (Except for Me and my Monkey)” by The Beatles.

70

Figure 3.17. Open-string ascending minor thirds, “Love Me Two Times” by The Doors.

Figure 3.18. Open-string descending minor thirds in the guitar part of “Break on Through” by The Doors.

To contextualize the performative implications of the corpus study, Figure 3.19 models the top eight directional note transitions on an abstract fretboard. Each numeric node represents the number of half steps from the performative center in black, under the 71 assumption of tuning by fourth. Extrapolating further on fingering choice, descending minor thirds and ascending seconds and fifths correspond to a departure from the index finger in fretboard space, while ascending minor thirds and descending seconds and fifths correspond to a departure from the smallest finger. Transition by perfect fourth meanwhile shifts the performative center up or down one string. As a sequence of note transitions, associated pitches evoke a minor pentatonic collection.

To be clear, the transitions represented in Figure 3.19 are representative of the actual distances used to articulate the surface-level bass-note pitch transitions expressed in the

Modal-Pentatonic corpus. Larger transitions are relatively scarce. Earlier examples demonstrate anecdotally that cross-form harmonic-physical transitions are markedly larger than internal transitions. In comparing transitional averages, this trend is reflected across the Modal-

Pentatonic corpus—the aggregate average fret distance is 1.014 frets, but when only internal note transitions are considered, the resulting average is decidedly smaller at .879 frets.33 To better model the general performative characteristics of formal sections, only internal transitions are reported in Figure 3.20, alongside a module’s most common types of pitch transitions.

33 In a study presented at the 2019 annual meeting of the Society of Music Perception and Cognition, I demonstrated that pronounced gestures in the Modal corpus can effectively predict changes in form at a level of statistical significance (Shea, Glowacki, and Shanahan 2019). See de Clercq 2017 (154) for a straightforward explanation of probability values as used in music theory research and studies on form.

72

Form: Function and Performance Practice

Transitional data is also useful for investigating standing intuitions about form and formal function. As Summach (2012, 2) asserts, general listeners recognize formal organization implicitly through sustained exposure. This process contributes to a model of formal expectation (Huron 2008), where listeners develop an understanding of a formal section’s functional identity and syntax (i.e., relation to other forms), and use this knowledge to orient themselves in musical time. Again focusing on songwriting process, the following discussion investigates how songwriters relay the characteristic features of formal modules through fretboard performance.

Summach sorts modules into three categories: primary, secondary, and auxiliary.

Primary modules contain “a song’s principal materials” (327) or text with the most rhetorical significance, namely A (strophe/refrain) and C (chorus). Secondary modules provide a functional departure from the primary module, including B (bridge), V (verse), P

(prechorus), and Z (postchorus). Primary and secondary module types are considered to be

“core” modules. All others, such as I (intros), O (outros), and Ie (instrumental interludes, not defined by Summach but treated here), are categorized as auxiliary, since they are “not included among a song’s primary or secondary modules” (326).

73

Fret ß smallest finger center index finger center à

3 5 7 String -2 2 2 -7 -5 -3

Figure 3.19. Top-eight most-frequent pitch transitions modeled by fingering on a guitar fretboard.

74

Module type Module Count Avg. fret dist. Freq. pitch motion Secondary verse 154 0.913* 2, -2, 3 Primary chorus 138 0.864 2, -2, 3 Auxiliary intro 56 1.21* 2, -2, 3 Auxiliary outro 51 0.838 2, -2, 5 Primary refrain 40 0.659 -2, 2, 3 Auxiliary interlude 34 1.55* 2, -1, 7 Primary strophe 28 0.483 2, 3, -5 Secondary prechorus 27 1.19* 2, -3, -7 Secondary bridge 21 0.907* 2, 3, -2 Secondary post-chorus 9 0.844 2, -2, -3

Figure 3.20. Stylistic components of the Modal-Pentatonic corpus by formal section (inter- formal transitions only). Asterisks note an above-average rate of performative transitions.

The verse-chorus (VC) cycle is perhaps the most widely recognized pair of related modules, steadily proliferating on the Billboard Top 40 charts from the 1960s onward (108).

Conveyed in Figure 3.20, the performative tendencies of the verse curiously match those typically attributed to the chorus. As Summach states, “The primary formal status of C also tends to be reinforced by some combination of intensifying features: for example, a more dense or active instrumental texture” (106). With a higher than average rate of fret transition, both listeners and performers might perceive verses in the Modal-Pentatonic corpus as demonstrating a greater degree of auditory complexity than is typical. In terms of heard and performed bass-pitch transitions, however, both modules prioritize transitions by ascending/descending step and minor third. Thus, the harmonic characteristics that

75 distinguish verses from choruses may occur outside of guitar chord patterns, and the burden of textural function may be relegated to the melody or other instrumental parts.

Unlike verses and choruses, strophes and their refrains are less performatively active modules. This tracks with the formal-stylistic features of the Modal-Pentatonic corpus, where the majority of songs with strophes are in the blues genre. As such, relatively little gestural distance is traversed as the performer navigates a perfect fourth (i.e., a performative step on the fretboard) from the I to the IV chord. Blues influences are also reflected by pitch motion in the refrain, as it is the only module to feature a descending second as its most frequent harmonic-formal transition, specifically to articulate the blues cadence transition from V to

IV. Similarly, the use of ascending minor thirds and descending fourths in strophes suggest that the IV chord could be approached by minor third and then major second, before descending by perfect fourth back to the I chord, similar to the pitch transitions illustrated in

“Radar Love” above (Figure 3.15).34

Prechoruses are recognized by their “momentum-building” features (Summach 2012,

107) brought on by an intensification of Meyer’s secondary parameters such as timbre and texture. Perhaps unsurprisingly, the data suggest this module is the most performatively active. Interestingly, prechoruses are also the only module to feature primarily descending pitch motion (in pitch space) in the form of descending minor thirds and fifths. This is puzzling, as one might expect increases in pitch height to contribute to the build toward a chorus, as is

34 These claims warrant further investigation within the context of global and local key centers and in a broader sample of strophe-based songs. The described note transition of a minor third would also not necessarily constitute a change in root and would instead be understood an appregiation to another chord tone. However, there are most certainly songs that do use the lowered minor third as a chord root (“Back in the USSR” by The Beatles comes to mind, where the chord progression is Am-Dm-C in the verse and Am-C-Dm in the chorus).

76 the case with the prechorus of “My Sharona” by The Knack. Other prechoruses, such as the one in “Smells Like Teen Spirit” by Nirvana, build momentum through pitch repetition, resulting in a relatively low average fret distance. It may be that the prevalence of descending fifths reflects the use of a circle-of-fifths sequence like the one featured in “We’re An

American Band” by Grand Funk Railroad. Descending bass-pitch motion by third and fifth may also be perceived as stronger or more active due to the introduction of new pitches in the following chord’s collection. Ascending thirds and fifths, on the other hand, are potentially weaker because the following chord roots are members of the preceding chord.

Overall, intuitions theorists have about form are supported by this study. For example, introductions and instrumental interludes are expectedly more performatively active. Their most frequent types of bass-pitch transitions also provide contrast from other modules, by the prevalence of descending minor seconds in interludes. The data, however, also present harmonic curiosities that should be investigated further. Verses, choruses, and introductions, for example, all feature the same types of most-frequent pitch transitions.

Why might this be? If the issue is approached from a songwriting standpoint, perhaps these modules are a first step in the compositional process and the overused transitions act as a frame of reference from which other modules are composed. That is, on the basis of formal contrast, these rhetorically focused modules embody the norms of compositional practice for modal rock songs, while others necessarily express other functionally identifying features on the basis of formal contrast.

77

Predicting Changes in Form

The data provided by the Modal-Pentatonic corpus also permits a statistical assessment of the Transition performance practice principle as the relationship between pronounced physical gestures and formal segmentation. As illustrated in “All Day and All of the Night” and “I Believe in a Thing Called Love,” these songs suggest that the largest gestures in instrument space most often occur across formal boundaries. Another underlying argument is that pitch-class distance (i.e., mod-12 inversional pitch symmetry) often obscures or is not reflective of the performative shifts in pitch that occur on the surface of rock. However, because of the recursive nature of pitch on the electric guitar fretboard, it is also hypothetically possible to traverse a physical distance without technically shifting in pitch space, as is the case in the two voicings of a C7 chord illustrated in the previous Figure 3.4.

In response, the following section outlines a model designed to assess the relationship between non-reductive pitch space and performative distance as it relates to formal segmentation, to determine if either are effective predictors of formal transition.

Figure 3.21 provides a density plot of pitch-space transitions in the Modal-Pentatonic corpus. Pitch distance is calculated using MIDI values for pitch frequency; for example, the pitch C4 holds the MIDI value 60. To calculate distance, differences in MIDI values are taken sequentially. The overabundance of zeroes indicates that, most often, notes are repeated. This is also reflected in Figure 3.22, which plots Euclidean distance at a note-to- note level. Unlike Figure 3.21, the Euclidean distance data is non-directional—due to the

Cartesian formula, all values are reported as positive. Because of this, the Euclidean distance

78 data are non-normal, or not distributed equally around the mean as with pitch distance, which requires a non-parametric statistical approach.

Figure 3.21. Density of note-to-note pitch distances in the Biamonte Modal-Pentatonic corpus.

79

Figure 3.22. Density of note-to-note Euclidean distances in the Biamonte Modal-Pentatonic corpus.

The following Generalized Linear Mixed Effects Model is a non-parametric statistical model:

Formal transitions ~ Euclidean distance + pitch distance + (1|gap/no gap)

This model determines if changes in Euclidean distance and/or pitch distance are predictive of moments of formal transition, while also taking into account the random variable of a 80 metrical gap. Moments of formal transition are treated as the single transitory event between formal sections as encoded by the analysts where Euclidean and pitch distances is calculated.

The gap/no-gap random variable meanwhile takes into account Fitts’s Law to determine if a performer is provided with ample time to make a large leap. The data treats a gap moment as one featuring a measure or more between note values.

Figure 3.23 illustrates how the model hypothetically applies to the transition from verse 1 to chorus 1 in “Crazy On You” by Heart. There, the Euclidean distance from (15, 5) to (2, 2) results in a performative transition of 13.34 frets and a MIDI-value pitch distance of

-41.35 In this case, the model does not consider there to be a gap in the texture, as there is only a single eighth note between D4 and A2. By assessing moments such as these, the model essentially asks “Do pronounced shifts in physical and pitch distance occur across changes in formal zone with such consistency that they are reliably indicative of formal transitions?”

35 Note that the underlined integer in (fret string) indicates the open-string note has been substituted for the next fretted note. 81

Figure 3.23. The generalized linear mixed-effects model considers the Euclidean and pitch distance values calculated by the pitch transition over the double bar, from verse to chorus. “Crazy On You,” by Heart.

The results of the generalized linear mixed-effects model suggest that both Euclidean and pitch distance are effective predictors of formal transition when considering the random effect of a metrical gap between note transitions (binomial glme, n = 40,321 transitions;

Euclidean distance, p < .001; pitch distance, p < .001). Figure 3.24 summarizes the results of the model. As shown, Euclidean distance has a small but positive effect on formal transition

(r = .17), while pitch distance has a negative and even less impactful influence (r = -.05).

Both values indicate that the overall predictive power of Euclidean and pitch distance for form is statistically significant but are possibly strengthened by other factors included in the corpus but not considered by the model, such as rhythmic value, tempo and note duration.

82

Mixed-Effects Model Estimate Std. Error z-value P-value Intercept -3.204 .960 -3.336 < .001 Euclidean .170 .016 10.641 <.001 Pitch -0.049 .006 -8.813 <.001

Random Effects Variance Std. Dev. Gap 2.261 1.504

Figure 3.24. Generalized linear mixed-effects model to predict moments of formal transition via Euclidean and pitch distance, with the random variable of a metric gap between notes in the Modal-Pentatonic corpus.

Caveats and Future Work

When analysts investigate the compositional nuances of a single work, they draw closer to understanding the creative agency of an individual composer. Following Meyer’s

(1989) characterization, our close reading of “All The Day And All Of The Night” and “I

Believe in a Thing Called Love” reveals Davies’s and Hawkins’s compositional and performative idioms (33). Corpus studies, on the other hand, operate at a broader scope. If the scope is properly narrowed, as Gjerdingen 2014 advocates, then our investigation of modal rock conveys the stylistic dialect of rock guitarists who primarily composed and performed in the 1960s and 70s (Meyer 1989, 34).

Both levels of analysis—the micro and the macro—are necessary for a holistic understanding of musical style. But despite the evidence presented in this chapter, these analyses only provide a constrained perspective: at most, explicated were the performative tendencies of Anglophone rock music of the mid- to late-twentieth century as a genre of music. To test if the outlined performance principles transcend genre as stylistic paradigms,

83 the scope of this investigation must be comparatively expanded. Diversity, not homogeneity, is critical to this pursuit.

General listeners, now more than at any point in history, are being exposed to a more diverse palate of musical genres and artists through the proliferation of streaming services such as Spotify.36 These platforms have specifically created a space for artists who are otherwise overlooked in traditional measures of success, such as radio time and record sales, to be easily accessed by the public. As such, I am not convinced commercial success as a metric for analytical focus in music theory analysis is the best way forward for a holistic understanding of style, as reflected by current listening practice.

A demographic survey of the 121 artists featured in the Rolling Stone 200 corpus reflects the effects of such a focus: white male artists are represented most prominently (n =

64, 53%), followed by non-white male (n = 34, 28%), non-white female (n = 13, 11%) and white female (n = 10, 8%) artists. A considerable percentage of songs from the RS200 corpus are also concentrated in the 1960s (n = 86, 43%). Just as well, the Modal-Pentatonic corpus presented here admittedly subscribes to the same issues: only three of the groups feature female artists (Nancy and Ann Wilson of Heart, Christine Hynde of The Pretenders, and Patti Smith), ten percent of songs (n = 5) are by The Beatles, and much of the corpus’s songs were recorded in the late 60s and early 70s.

36 Spotify (https://insights.spotify.com/no/2017/11/02/listening-diversity-spotify/) reports substantial increases in hours streamed (+25%) and average number of artists played (+37%) from the years 2017 to 2019, while Billboard year-end charts (https://www.billboard.com/charts/year-end/2017/streaming-songs-artists) show that more than two-thirds (72%) of the 25 top-streamed artists in 2016 and 2017 identify as a minority (n = 32) or are women (n = 9). 84

From this data it is clear that music theory’s continued focus on mainstream rock neglects the contributions of female, African American, and other historically under- represented artists who have otherwise made significant contributions to the style. This includes those on the fringe of our historical scope, such as early rock pioneers Sister

Rosetta Tharpe and Memphis Minnie or contemporaries such as Brittany Howard and Annie

Clark. Each of these artists are exemplars of rock, and their guitar performances present some of the strongest evidence for a gesture-based theory of function.37 However, due to the recurring emphasis on commercially successful rock songs, these artists are rarely included in popular music databases. In short, these artists lack representation in analysis. Due to the issues outlined, each component of the following chapters actively prioritizes the contributions of underrepresented pop-rock musicians to better reflect the diverse listening habits of modern listeners and to foster a methodological precedent for diversity and inclusion in pop-rock analysis.

Works archived on ultimate-guitar.com provide a potential “presentist” (Gjerdingen

2014, 192) solution to issues of stylistic and social diversity, at least by offering a more modern collection of songs and a wider swath of artists than just those lucky enough to have risen to the level of widespread commercial success. As shown in Figure 3.25, the majority of songs found on ultimate-guitar.com were also composed from the 1990s onward, in contrast to the Billboard and Rolling Stone corpora.

37 Video performances by Sister Rosetta Tharpe in the PBS documentary Sister Rosetta Tharpe: The Godmother of Rock and Roll highlight that Tharpe’s guitar solos mostly occur in a relatively constrained area of the fretboard. However, Tharpe was also known to use of unconventional tunings, which could potentially influence the harmonic affordances of her instrument. See (https://www.pbs.org/video/american-masters-watch-sister- rosetta-tharpe-godmother-rock-roll/). 85

Figure 3.25. Comparison of historical distribution between Guitar Pro files archived on ultimate-guitar.com and the encoded songs in the McGill-Billboard and Rolling Stone 200 corpora. 86 Summary and further application

This chapter presents evidence to suggest that the surface-level stylistic features of rock songs are generated by performers and songwriters in response to the ecological affordances of the electric guitar. Application of the presented embodied model of function also demonstrates its malleability—enough so for a comprehensive investigation of style and performance practice at the level of close reading and empirical analysis. The next chapter generalizes beyond the genre of modal rock to a historically and stylistically broader collection of pop-rock songs. A survey of approximately 8,000 transcriptions provides a baseline of stylistic features (pitch, rhythm, texture, instrumentation) to offer a much-needed measure of surface-level ground truth in contemporary popular music. This data then contextualizes the performative and stylistic tendencies in a subset of 434 pop and rock songs, which are encoded for formal organization in the same manner as the Modal-Pentatonic corpus.

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4. Chapter 4: Stylistic Ground Truth in Popular Music

The compilers of current popular-music databases such as the Billboard and Rolling

Stone 200 employ a “top-down” approach to musical organization (Burgoyne 2011; de Clercq and Temperley 2011). Using reductive techniques, the researchers analyze the harmony and form of the corpora’s songs to provide a symbolic-temporal framework meant to emulate a listener’s perceptual experience. However, as discussed earlier in the dissertation, harmony is not necessarily accessible to general listeners (Pollard-Gott 1983). Instead, it is shown that listeners tend to rely on extra-thematic features such as auditory complexity, texture, and timbre to make distinctions about music’s functional organization; for example, the perceptible differences between a verse and a chorus due to changes in rhythmic energy.

Harmonic patterning also shares an irreducible relationship with surface-level performative concerns. Chapter 2 demonstrates this explicitly, illustrating that the affordances of the guitar are perhaps a generative force behind chord bass-note pitch transitions in modal rock and that performative gestures and syntax are also an effective predictor of rock’s formal organization.

Because popular music is a style consumed by millions of general listeners every day, and in response to the increased diversity in artists and genre that the average listener experiences when engaging with music streaming services, this chapter disengages from reductive methods of corpus creation and analysis, on principles of accessibility and in

88 pursuit of stylistic ground truth.38 It instead presents a curated collection of full-scored digital transcriptions of popular-music songs (complete with rhythmic, textural, and instrumentation information) in various notational formats to provide a previously unobtainable measure of the moment-to-moment extra-thematic and performative characteristics of popular music. Detailed in the following section are the motivation and methodology employed in creating this database, followed by a discussion of the resource’s numerous potential applications in future studies on style, performance, and analysis in popular music.

Accessibility in Methodology

The rich scholarship that has developed from studies of current popular-music corpora notwithstanding, the materials and scope of the Billboard and Rolling Stone databases do not innately afford analyses based on the intersection between Meyer’s primary and secondary parameters. And in their creators’ defense, the corpora were never designed for such a task. Burgoyne’s (2011) goal in developing the Billboard is to provide symbolic and continuous timepoint data for training a feature-recognition algorithm, to advance music information retrieval research. de Clercq and Temperley (2011) meanwhile frame their corpora as a tool for style analysis and readily admit a large portion of its materials are still

38 Music information retrieval research defines musical “ground truth” as symbolic data used to train and classify other symbolic data (Sturm and Wiggins 2018, 1-3). The term most often applies to feature extraction from recordings, as in Burgoyne 2011, but here I use it to suggest that the surface-level pitch, rhythmic and instrumentation data can eventually be used for similar tasks such as categorizing harmony or determining style or genre. These goals, however, are outside the scope of this study and I reserve them for future work.

89 being developed. Nevertheless, their emphasis on harmony as a measure of style proves curious.

Following Meyer’s (1989, 33–36) definition, the primary and syntactic parameters of style in eighteenth-century music are harmony, melody, and rhythm, in that they are segmentable, provide perceptual closure, and express non-uniformity (i.e., can be sorted into discrete hierarchical identities). Articulation, dynamics, texture and timbre are meanwhile secondary and statistical parameters of style due to their inability to do the same perceptual tasks. Moreover, Meyer argues that the latter often shape the former in common-practice music. However, throughout his study Meyer also makes it clear that music from the nineteenth century onward relies more heavily on statistical (i.e., secondary parameters)— that is, the agency of secondary characteristics such as texture and timbre to evoke perceptual segmentation is increased, while the functional efficiency of harmony, melody and rhythm is either maintained or falls away.

As discussed in chapter 2, White and Quinn (2018) provide specific evidence for the latter trend in popular music, demonstrating that—compared to common-practice music’s harmonic patterning—popular-music harmony is significantly more diffuse and, more importantly, is functionally style dependent. By this measure, de Clercq and Temperley are perhaps justified in working toward a better understanding of one of popular music’s more ambiguous parameters of style. But at the same time the authors do overlook many of the analytical obstacles and caveats that go along with such a focus. Overall, by merit of their reductive methodology and materials, their findings represent a structural understanding of popular music that is perhaps only accessible to expert listeners, in contrast to the general

90 accessibility of secondary/surface-level features of style, which Meyer argues provides increased perceptual segmentation in post-eighteenth-century works.

To summarize, I highlight outlines four issues surrounding current empirical approaches to popular-music analysis. Current popular-music corpora are limited in their accessibility, as they [are]:

1. reductive, focusing on harmony as a parameter with limited perceptual accessibility to general listeners and one not necessarily prioritized by songwriters.

2. historically constrained, focusing on works from the mid-1950s to the early 1990s, with an emphasis on songs in the late 1960s and early 1970s.

3. skewed toward rock, which in combination with the above deprioritizes post- millennium pop music.

4. over-represent certain artists, due in part to their comparatively narrow historical and stylistic scope and their focus on critical acclaim or commercial success.

Each of these issues occur in corpora that are unintentionally disposed toward songs written or performed by white-male rock artists. But as advocated at the end of chapter 3, the stylistic contributions of minority artists on development of rock is undeniable, even as these artists are not represented in commercial or critical measures of success.

Again, the creators of the Billboard and Rolling Stone corpora are not necessarily interested in the intersection between pitch and popular music’s surface-level musical features such as rhythm, texture and timbre. Nevertheless, this also means that their materials and scope are not compatible with the goals of this dissertation. I develop a new corpus of popular music, the Pop-rock Function corpus, in response. The Function corpus

91 samples from a broader but collated collection of crowd-sourced transcriptions titled the

Pop-rock Features corpus.

The Features corpus is a corpus full-textured pop and rock songs (n = 3,714) from the 1950s onward which prioritizes equity in artist distribution (n = 1,107 artists, no more than 5 songs by a single artist). These transcriptions offer surface-level features that are easily assessed via computational analysis of exported file types (e.g., MIDI, krn, musicXML, etc.).

As described later in this chapter, this data in coordination with metadata are useful for addressing issues of genre categorization using machine-learning methods. However, unlike the Modal-Pentatonic corpus from Chapter 2, these songs are not thoroughly examined for notational errors and thus there are fewer guarantees about their quality, even as their transcriptions are highly rated by the ultimate-guitar.com community.

The Function corpus is a subset of the above sample and is hand-encoded for formal organization, similar to the Biamonte Modal-Pentatonic corpus. Critically, it is even more balanced than the Features corpus: the collection contains an equal number of socially- determined “pop” and “rock” songs (n = 250 each) and its historical distribution (per decade) is modeled on the original ultimate-guitar.com repository, again because the latter provides more works for study post 1990 than existing corpora. In response to the issues of social representation created by a focus on commercial success, the Function corpus not only features more artists than the Rolling Stone or Billboard, but also prioritizes historically underrepresented artists such as women, non-binary, racial and ethnic minority songwriters and performers. Finally, like the Modal-Pentatonic corpus, analysts carefully assess songs in the

Function corpus for quality and hand-encode its formal organization.

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Pop-rock Features Corpus

Songs and their metadata included in the Pop-rock Features and Function corpora are extracted from ultimate-guitar.com using web-scraping tools.39 The website’s interface conveniently allows one to sort user-generated transcriptions of popular-music songs according to a variety of parameters, such as file type, rating, and genre. As with the Modal-

Pentatonic corpus, all songs must first meet the baseline requirements of being encoded

Guitar Pro format and rated 4 out of 5 stars or higher by the ultimate-guitar.com community.

Currently there are 189,762 songs in Guitar Pro format archived on ultimate-guitar.com.

However, only 1,000 songs can be downloaded under each sorting parameter, presumably to prevent one from easily retrieving the website’s entire collection at once. For example, after selecting the Guitar Pro file format category, ultimate-guitar.com reports that there are 67,374 songs available to download that fall under the “rock” genre.40 But when this genre is selected and the songs are sorted by rating (highest to lowest), only 20 pages of rock songs

(50 songs on each page) are accessible.41 This constraint is partially circumnavigated by further segmenting the collection by the “Decade” parameter. In doing so, 1,000 of the top-

39 Song metadata and their URLs were retrieved using Lynx from the Mac OS terminal. The Guitar Pro files were then downloaded from the scraped URLs with the Python packages Chromedriver and Selenium, again ran from the terminal. 40 All references to “rock” and “pop” in this chapter refer to the user-submitted genre classifications provided on ultimate-guitar.com. In doing so, I attempt to sidestep the notable social and racial issues surrounding genre categorization in popular music. For example, Johnson 2018 demonstrates that platforms such as the Billboard charts and Spotify have historically cast African American artists under umbrella terms such as “soul” or “hip- hop,” thus leading to a reality where “the history of style and musical taxonomies is inherently racialized” (17). This study sits somewhat outside of Johnson’s work in that I aim to assess the (perhaps) broader perceptual differences between “pop” and “rock” as style, not genres, with a keen awareness that even these labels, and indeed my resource of choice (ultimate-gutiar.com), still likely de-prioritize certain groups of artists. I attempt to mitigate this potential oversight drawn on by the biases of style by prioritizing the works of historically underrepresented artists in the Function corpus, as discussed in the following “Demographics Encoding” section. 41 The page count does not go past 20, even when manipulating the URL in the search bar. 93 rated rock songs in Guitar Pro format are selected from each decade, from 1960 onward.42

The same procedure is conducted for songs labelled under the pop genre, resulting in 8,909 songs from which the Pop-rock Features corpus is generated. This sample, however, still requires parsing by instrumentation, genre and song duplicates.

At least a quarter of the of the ~9,000 downloaded files contain only two instrumental tracks or less (n = 2,182). Because instrumentation is believed to have a notable impact on genre categorization (Sturm 2012), and single-instrument textures are not reflective of the instrumentation of most popular music, these songs are excluded. Category labels also present issues. Many of the remaining songs are categorized under both pop and rock genre categories (n = 134). These songs are currently set aside in a reserve dataset for future study. Finally, because ultimate-guitar.com transcribers can submit competing versions of the same song to be rated by the community, 1,215 unique songs exist in duplicate versions. To choose the ideal version, duplicate songs with the most votes are prioritized first. If two separate versions of the same song feature a difference of five votes or less, the song’s rating is considered instead. Through this process, a total of 5,393 unique songs remain; specifically from parsing the original sample by instrumentation (three or more instruments) and genre categorization (either pop or rock, not both), and then selecting only the most-voted on and highest-rated versions.43

42 There are comparatively fewer songs available from the 1950s (n = 56 pop, n = 95 rock). 43 Approximately 10% of songs sampled (n = 585) do not have voting or rating information. Their metric for inclusion under ultimate-guitar.com’s rating system is therefore unclear, but I suspect download frequency is a factor in why they were listed for download when sorting by song rating. However, I do not have data to support this claim, even as they are still included in the sample described above. 94

The next operation balances these 5,393 songs around artist. Songs are divided by

“pop” (n = 1266) and “rock” (n = 4127), then sorted into decade composed (1950 to 2010), resulting in 14 sub-samples: 7 decades of rock songs, 7 decades of pop songs. Artist overrepresentation is addressed in these sub-samples by randomly sampling no more than five songs per artist, to avoid any biases of popularity or commercial success. Importantly, all artists included in the previous 5,393 are still included in the final sample, with the only difference being the number of times their songs occur. The Pop-rock Features corpus (n =

3,731 songs) is formed from this final sample. General statistics for the Features corpus are reported in Figure 4.1, in comparison to the original sample.

Pop-rock Features Original Sample count proportion count proportion Genre pop 1077 29% 2697 30% rock 2654 71% 6211 70% Decade 1950 38 1% 145 2% 1960 239 6% 1216 14% 1970 501 13% 1255 14% 1980 648 17% 1447 16% 1990 640 17% 1304 15% 2000 939 25% 1880 21% 2010 726 19% 1543 17% Artists 1107 1250

Figure 4.1. Song count and proportion between sample and final Features corpus.

Overall, the distribution of works by genre and decade in the Features corpus is generally reflective of the original distribution of songs archived on ultimate-guitar.com. This is

95 demonstrated in Figure 4.1, where the data show no more than a 5% difference between historical period (with the exception of the 1960s, which are again over-represented) and a

1% difference between genre. As is the case with the Rolling Stone 200, both utlimtate-guitar.com and the Features corpus skew toward rock. Given that some researchers qualify rock as primarily guitar-driven music (Biamonte 2010; Nobile 2014), this is perhaps unsurprising from a website designed specifically for guitarists. The utility of this dataset is intended for machine-learning studies and as a general resource for musicians, so the described imbalances are perhaps less concerning. More critical to the goals of the corpus is that no single artist is grossly overrepresented, even if their most popular songs are potentially overlooked through random sampling.

Pop-rock Function Corpus

The Pop-rock Function corpus is a collection of 434 songs balanced around artist representation and genre. Its purpose is to afford multi-parameter music-theoretic investigations of function between performance practice, formal organization and surface- level harmonic and textural patterning in songs and by artists not typically included in current discourse. The following section describes the methods and challenges in forming the corpus, including ascertaining artist identity, creating a balanced collection of songs, and analyzing and encoding formal organization.

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Diversity in Sampling

So far the dissertation has not addressed explicitly how issues of diversity and inclusion are treated in the described corpora. But before proceeding, it is also pertinent to outline why such steps toward inclusion are necessary. At the end of chapter 3, I provide evidence that suggests that minority and women artists are underrepresented in the Rolling

Stone 200 which, next to the McGill-Billboard database, is one of music theory’s most-utilized popular-music corpora. In this section, I also argue that black artists, in particular, have an undeniable influence on the development of the rock music featured in the Rolling Stone 200.

Evidence of the influence of black artists on rock music manifests most clearly in studies of genre taxonomy. Johnson 2018, drawing on genre classification models used by radio stations and record executives in the United States, demonstrates that the introduction of the “rock n’ roll” genre in the 1960s served to distinguish music performed by white artists from rhythm ’n’ blues songs by black artists. Johnson (38), in coordination with Redd

(1985, 41), argues that “[w]hiteness was ingrained in rock from the outset, and the regular practice of covering explicitly prevented black artists ‘from entering the large white consumer market by supplying consumers with recordings of white artists singing the rhythm ’n’ blues or black music of black artists.” In this way, Johnson argues that that “the history of style and musical taxonomies is inherently racialized” (17) and he and Redd both conclude that there is a historically propagated but false distinction between rhythm ’n’ blues and rock music. That is, though separated by record executives according to race, these musics are largely stylistically equivalent and, most importantly, originate with black artists.

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Basic statistical methodology maintains that with a more robust sample comes a better approximation of tendencies within a broader target population. For this study on style, style transmission, and production, it follows that a representative corpus should sample from as many artists as possible to approximate how replicative patterns of human behavior contribute to the development of a style (in this case, popular music). If black artists are regarded as the progenitors of rock music, but are underrepresented in current corpora, then it also stands to reason that existing corpora demonstrate an inherent sample bias toward white artists. And while there is an argument to be made that one artist may be more paradigmatic of a style than another, no one artist or ensemble (e.g., The Beatles) is solely responsible for the formation of a style. For these reasons, I find it necessary to ensure that the Function corpus and any samples for testing from the corpus reflect a balance of artists from non-homogenous racial and ethnic backgrounds.

Demographic Analysis

There is an innate incompatibility between the permeable boundaries of human physical and social characteristics and the binarity required in methods of empirical encoding. Such disconnect is made particularly clear when considering the components of intersectionality as a framework for why one artist may be prioritized over another in music analysis. Intersectionality is defined broadly as “the complex, cumulative manner in which the effects of different forms of discrimination combine, overlap, or intersect, especially in the experiences of marginalized individuals or groups” (Crenshaw 1989; Merriam-Webster

2019). By this definition, a gamut of personal characteristics or practices can contribute to

98 artist discrimination, including race, education, sexuality, age, gender, ethnicity, and culture.

Glenn (2002) adds specificity to the nature of intersectionality, arguing that its categories are inherently relative but that traits such as gender and race can be treated as “anchor points” even as they are not static (14).

Given this multi-variate flexibility, it becomes incredibly difficult to take a completely holistic approach to intersectionality when forming an intentionally representative resource.

That is, how does one decide exactly which factors to consider when attempting to increase representation of marginalized groups in popular-music analysis? Moreover, which individuals or groups are “diverse enough” for qualification as underrepresented?

Broadly, I approach this issue by using the overrepresentation of white-male artists as an antithetical metric: individual or groups of artists (e.g., a band) whose members are primarily non-white or non-male are considered to be underrepresented in popular-music analysis. This categorization by race, ethnicity, and gender is described in more detail below.

This dissertation pursues the task of increasing representation to the best of the author’s ability, with the understanding that the methodology described considers a comparatively narrow band of parameters to identify marginalized or minority artists.44

Two overarching categories are used to distinguish over- and under-represented artists in the Features and Function corpora, under the umbrella term “minority status” as used by Laurie and Kahn (2017) to indicate any individual that is subject to societal marginalization. The first minority status category considered is gender, which is separated into three sub-categories: male, female, and non-binary. The latter category encompasses

44 As such, I preemptively welcome any criticism for refining the described techniques in future work.

99 persons who do not necessarily identify with the gender they were assigned at birth, including transgender persons. By extension, it is thereby assumed that artists who are categorized as male or female identify with the gender they were assigned at birth. Both female and non-binary artists are qualified as under-represented by this study.

The second minority status category considers race and ethnicity as its primary parameters. These two parameters frequently overlap, but their distinction is critical, even as both have contributed historically to marginalization. This study treats an artist’s race as a socially determined distinction between human groups based on “perceived common physical characteristics” that are inherent from birth (Cornell and Hartmann 1998, 24).45 In contrast to most facets of ethnicity, race is primarily externally imposed on marginalized persons, such as by white Europeans as they conquered and enslaved African peoples (ibid.).

In this study, artist ethnicity “…is defined as a sense of common ancestry based on cultural attachments, past linguist heritage, religious affiliations, claimed kinship, or some physical trait” (Cornell and Hartmann 1998, 19). Hispanic or Latino persons, for example, are treated by the United State Census as belonging to an ethnic category,46 while White, Black/African-

American, American Indian or Alaska Native, Asian, and Native Hawaiian or other Pacific

45 Further distinctions between race and ethnicity are summarized at (https://plato.stanford.edu/entries/race/). Last modified February 17, 2016. 46 In 1997 the Office of Management and Budget, responding to “the increasing diversity of our Nation’s population” (Section B, paragraph 12), determined that there were to be two categories for data on ethnicity: “Hispanic or Latino” and “Not Hispanic or Latino.” See Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity: (https://www.whitehouse.gov/wp-content/uploads/2017/11/Revisions- to-the-Standards-for-the-Classification-of-Federal-Data-on-Race-and-Ethnicity-October30-1997.pdf) 100

Islander are all considered racial categories.47 When categorizing artists, I do not distinguish artists who are multiracial or multiethnic (such as Beyoncé) from those that are not.

Other identifying and potentially marginalizing characteristics such as sexuality, level of education, and age are not considered by this study in its current scope. However, efforts are made in the following encoding process to note relevant characteristics when observed.

For example, the artist Adam Lambert is bisexual, but under the current metric this does not qualify him as an underrepresented artist.

Demographic Encoding

This study approaches the distinction of minority status through the use of online and publicly accessible information, such as artist profiles hosted on Wikipedia, artist or band websites, and online magazine and video interviews. When an artist’s demographic category cannot be ascertained from written resources, the artist or group is not categorized.

To be clear: an artist’s outward or observable characteristics as conveyed through photographs is not considered as a valid metric of demographic assessment. Artist information is encoded by a small team of graduate and undergraduate students, including the author.48

To achieve a meaningful measure of representation in the final corpus, proportional membership and agency of underrepresented ensemble members are considered. For

47 The utility of the US Census categories is subject to discussion, as they are frequently employed in studies on the social construct of race (Ifekwunigwe et al 2017) but are also argued to further discrimination in political practice (Nobles 2000). 48 As the author, I accept all responsibility for any mis-categorization of artists that results from the described procedure and will work to correct any errors as they are presented.

101 example, some musicians are solo artists who perform with a rotation of studio and touring musicians (e.g., Adele), while others are members of a relatively consistent contingency of musicians (e.g., the band Heart). For this study, a group is considered primarily underrepresented if 1) more than half of its members meet minority status by race, ethnicity, or gender or 2) if the public-facing or title member of the ensemble meets minority status by race, ethnicity, or gender (e.g., Rihanna). The former measures primacy by proportion, while the latter does so by artist agency. There are, however, ambiguous cases where artist proportion and agency are at odds. In the band Heart, for example, Nancy and Ann Wilson are founding members and contribute to the ensemble’s songwriting (agency), but their three other bandmembers are white and male (proportion). Therefore, does categorizing Heart as primarily underrepresented in popular music conflict with the pursuit of diversity and inclusion held by this study? It seems not, given the creative agency of the Wilson sisters. In cases such as these, the encoders use their own discretion to make such judgments, as supported by the evidence available to them, and subsequently mark the artist or ensemble as “ambiguous” when appropriate.

The following is a summary of the encoding procedure for solo artists and ensembles, as presented to the encoders:

SUMMARY

Goal: The goal of this encoding project is to increase representation for minority artists in popular-music analysis.

Minority: A minority artist is defined by this study as any artist whose identity is subject to marginalization. These include the characteristics or practices of race, ethnicity, religion, gender, sexual orientation, or disability (Laurie & Khan 2017).

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Categories: The scope of this study focuses on Race, Ethnicity, and Gender as markers of minority status.

Women: Women or female persons are considered by this study to hold minority status, even if they are not mathematically a minority, as women are consistently subject to marginalization in society.

Other categorizations: Other identifying characteristics that are societally marginalized (e.g., sexuality) should be noted when possible, even if they are not currently considered.

GUIDELINES FOR CATEGORIZATION

Race: a socially determined distinction between human groups based on “perceived common physical characteristics” that are inherent from birth (Cornell and Hartmann 1998, 24)

Ethnicity: a sense of common ancestry based on cultural attachments, past linguist heritage, religious affiliations, claimed kinship, or some physical trait (Cornell and Hartmann 1998, 19)

Gender: three current categories are employed: male, female, and non-binary. Male and female persons are assumed to identify with the gender they were assigned at birth. Non- binary persons explicitly do not identify with the gender they were assigned at birth.

PRIMARY STATUS

Solo artist: A solo artist is considered primarily minority if their identity aligns with any marginalized category under race, ethnicity, or gender. Solo artists can perform with bands but are ultimately the public face of the group.

Ensemble: An ensemble (e.g., a band) is considered primarily minority if half or more of their members' identities align with any marginalized category under race, ethnicity, or gender.

Ambiguity: Sometimes minority artists are the primary songwriter/composer of a group even if they are not the public face of the group and the majority of other band members (more than half) do not hold minority status. Analysts should use discretion, particularly when the minority artist holds a role of increased agency, such as the lead singer or is a founding member.

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CHECKLIST: PRIMARY STATUS

Agency: Does the minority artist hold a forward-facing role or is the title member of the group? Is the minority artist a founding member of the group or participate in songwriting?

Proportion: Do more than half of the members' identities align with minority status?

Each encoder is then presented with a sample of artists for practice analysis:

CHECK: ARTISTS

Backstreet Boys: Howie Dorough is Puerto Rican (ethnicity), however the rest of the ensemble is white/Caucasian. Not a primarily minority ensemble.

Arcade Fire: Founded by wife and husband Régine Chassagne and Win Butler. Rest of band is primarily white/male. Ambiguous, as Chassagne is lead vocalist/guitarist and a founding member.

Beach House: Pop duo Victoria Legrand and Alex Scally. Primarily minority ensemble, as half of members hold minority status.

Analysts are required to analyze five artists with the author’s guidance before proceeding on their own. A total of 273 (24%) artists hold minority status in the Features corpus (n = 1130 total artists), while the Function corpus features 212 songs (49%) by minority-status artists (n

= 434 total songs).

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File Format and Feature Extraction

Each song in the Features and Function corpora is exported, converted, and encoded in a variety of formats, including MIDI, krn, musicXML, and ASCII file types. Each provides digital materials to evaluate various parameters of musical style. For example, generic instrumentation data (i.e., instrument family type) is easily retrieved directly from

MIDI files. This proves advantageous in order to side-step inconsistencies and inaccuracies in the original Guitar Pro file, where some transcribers label instruments generically (e.g.,

“rhythm guitar”) while others provide the names of the performers (e.g., “Nancy Wilson”).

A handful of Guitar Pro files are also not encoded in English and, as such, instruments are labeled in other languages (e.g., “guitarra”). By converting each file with MuseScore’s batch

MIDI converter, instrumentation information is made uniform in format (e.g., “electric guitar” or “Rhythm Guitar 2” to “E. Guitar”).

MIDI data provide a utilitarian method for analyzing pitch and rhythmic content and are easily converted to other file formats. File types musicXML and krn are meanwhile less common outside of music research but are the standard for music-processing programs

Music21 and Humdrum, respectively. ASCII text files are unique to guitar tablature users, where a series of dashes and integers represent metric and fret information. As with the

Modal-Pentatonic corpus, I use ASCII tablature to make assessments about harmonic and formal function in guitar performance in the Function corpus.

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Function Corpus

The Function corpus is a curated sample of 434 songs taken from the Features collection. Working with the author, undergraduate and graduate student analysts provide formal information for the database. These annotations, in tandem with demographic and style data, support the subsequent stylistic analyses. The next section details the methodology utilized in shaping the Function corpus.

Form Encoding

Form encoding in the Function corpus follows a similar procedure to that outlined in

Chapter 3, but at a larger scale. Four musicians with overt fluency in the nuances of form and formal function in popular music worked in tandem with the author to encode form in the Function corpus. Broadly, this involved listening to the song on Spotify, determining the song’s formal organization, and matching these forms to measure numbers in the transcriptions obtained in GuitarPro format from ultimate-guitar.com.

Before beginning the encoding process, a training session was held, where each analyst was presented with the following definitions and asked to work with me to determine the form of songs together. These definitions are either taken directly from Summach (2012) or influenced by this study’s terminology:

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Formal modules

Use the following labels as you conduct your formal analysis.

Introduction – material that opens a song and precedes the core module (see above), some rock songs have multiple introductions.

Verse – a lyric-variant module type that “set[s] forth fresh lyrics with each iteration, supplying narrative or emotional context to the choruses” (106). Verses are self-contained (i.e., can stand on their own as a functional formal unit).

Chorus – a lyric-invariant module that establishes the “core message of the song.” Often reinforced by “intensifying features” such as increased instrumentation, background vocals, or changes in register (106).

Strophe – a lyric-variant module that contains a lyric-invariant refrain. Typically set to the same harmonic progression and features the same melody.

Refrain – a lyric-invariant module in a strophe, often the title of the song. Occurs at the end of the strophe (“tail”) but can also be positioned at the beginning (“head”). Repeated frequently, a refrain is “the pivotal sentiment or narrative detail in which each strophe originates or culminates” (20).

Note: Summach argues the refrain is a part of the strophe and cannot functionally stand alone. However, refrains often coincide with an audible change in texture. Please label refrains when you hear them.

Interlude – an extended instrumental section used to connect core modules. Contrasts from a bridge or solo in that it showcases a group of instrumentalists. Virtuosic displays are common, but not necessary. If one hears the same “solo” twice in one song, it is likely an interlude not a solo section.

Bridge – “a region of change and instability whose function is to reinvigorate interest and make the return of the chorus or strophe seem imperative” (61). Often marked a shift in harmony that culminates in a dominant-functioning chord to return to the verse, strophe, or chorus. Usually features a lighter instrumental texture and a quiet or low-register melody.

Prechorus – a module that builds expectation to the chorus is associated with specific momentum-building features, including melodic fragmentation, acceleration of harmonic rhythm, and movement away from the tonic harmony.

Postchorus – a module that occurs after a chorus and decreases the energy of the chorus in transition to a verse. Frequently features vocables (e.g., “ooo” “ahh” “ohhh”) and a thinning of instrumental textures.

Outro – closing material that occurs after core modules. Exhibits closing rhetoric, which includes the repetition of a core module (e.g., the chorus), thinning texture, and/or a fadeout.

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Solo – a module that usually consists of harmonic material from a core module (e.g., verse, chorus or strophe) and features a solo instrument (e.g., guitar, keyboard, saxophone). Unlike an interlude, only one instrument solos at a time while the rest act as accompaniment.

Tip: Often the final chorus of a song “becomes” the outro. In cases such as these, mark the outro as starting after the first full rotation of the final chorus.

Upon completing the training, each participant began encoding 100 songs randomly sampled from the Function corpus.49 This process resulted in an initial total of 500 songs, which were further parsed in the following ways.

Participants were also trained to be sensitive to specific issues when analyzing the form of the Features corpus. Like the Modal-Pentatonic corpus, each song should be free of overt pitch, rhythmic and formal errors; if a song contained errors, they were instructed to note the culprit song but proceed with the formal analysis of the original audio track.

Instrumental songs were also excluded from the final corpus, due to the innate ambiguity of labeling form. Finally, I also informed participants that they should listen for songs that are overtly racist or sexist, take note of these songs, and cease with the formal analysis as they would not be included in the final corpus.50 This process resulted in a final 434 songs. These songs are listed with relevant metadata in Appendix B.

49 During the encoding process, most of the student encoders remarked that many of the songs provided to them were “strange” or did not reflect an artist’s most popular works. This, unfortunately, is a byproduct of random sampling. In the future it is my goal to expand the Function corpus, which should provide a more representative sample of both mainstream and other works. This being said, I use random sampling as a tool to avoid biases of critical acclaim or commercial success to instead sample songs the ultimate-guitar.com community deems worthy of transcription. The impact of this approach is currently unknown, but I believe sets an important precedent in popular music to avoid continually revisiting the same works.

50 For example, the song “Chinese Rock” by The Ramones was immediately discarded from the corpus due to its racial insensitivity. See Hisama (1993) for a comprehensive discussion of race, ethnicity, gender and East Asian stereotypes in mid-century rock music.

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Descriptive Statistics

Like the original sample from ultimate-guitar.com, songs in the Function corpus coincide with metadata for style (pop or rock) and decade (1950–2010). These data coordinate with encoded form labels and performative distance and pitch information. Each song also features the earlier demographic assessment of artist identity as either primarily or not primarily underrepresented. Unlike the Modal-Pentatonic corpus, not every song contains a rhythm guitar part for testing. Of the final 434 songs, 351 or 81% contain a rhythm guitar part. Like before, a rhythm guitar part constitutes a non-solo guitar track with a relatively sustained rhythmic texture from which performance and pitch data are reliably retrieved.

Euclidean distance of performative transitions within the Function corpus is only slightly more active than those in the Modal-Pentatonic corpus (Function average: 1.057 frets,

Modal-Pentatonic average: 1.014 frets). In many ways, this data further support the Parsimony performance practice principle outlined in chapter 3. Figure 4.2 provides a density map of the transitions, demonstrating that the majority of transitions occur between 0 and 2.5 frets.

Because the Cartesian formula essentially flattens both horizontal and vertical directional data into positive values, the Euclidean distance data are non-normal.

Pitch distance is calculated directionally (i.e., ascending and descending) using MIDI values, as in chapter 3. MIDI data in the Function corpus are normally distributed around the mean and are thus suited for parametric testing. Again, due to the recursive nature of the guitar fretboard due to tuning, it is entirely possible (though potentially unlikely) to have a change in Euclidean distance but not pitch distance, hence the inclusion of zeroes in the

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Figure 4.2. Density of Euclidean (performative) distance in the Function corpus.

data. The reverse, change in pitch but no change in Euclidean distance, is not possible.

Figure 4.3 demonstrates the distribution of directional pitch distance in the Function corpus.

The Function corpus contains a total of 1,876 formal transitions between 11 formal types (e.g., verse, chorus, intro, etc.). These are the same formal types used while encoding

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Figure 4.3. Density of directional (non-mod) pitch distance in the Function corpus.

the Biamonte Modal-Pentatonic corpus, with the exception of srdc (statement, restatement, departure, conclusion).51 Figure 4.4 reports the transition probabilities of these formal types, where a transition probability is the statistical likelihood that one formal zone follows

51 This choice was intentionally made to prevent the student analysts from over-representing these formal labels, as the terms are often appropriate for more generic formal processes but require discretion in their use.

111 another. For example, verses are most likely to follow another verse (43%), in line with the two-part verse structure described in Summach 2012 and reflected in the srdc formal paradigm. A value of zero meanwhile indicates the transition does not occur at all in the corpus, such as the transition from an introduction to a postchorus.

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Bridge Chorus Interlude Intro Outro Postchorus

Bridge 0.105 0.234 0.105 0 0.098 0.043 Chorus 0.060 0.292 0.072 0.007 0.045 0.037 Interlude 0.063 0.251 0.093 0 0.024 0.027 Intro 0 0.023 0 0.879 0 0 Outro 0.055 0.170 0.044 0.003 0.118 0.027 Postchorus 0.023 0.256 0.081 0 0.064 0.105 Prechorus 0.052 0.262 0.060 0.005 0.029 0.029 Refrain 0.051 0.192 0.077 0.006 0.045 0.019 Solo 0.076 0.223 0.098 0 0.109 0.054 Strophe 0.025 0.233 0.092 0.031 0.043 0.006 Verse 0.026 0.184 0.057 0.035 0.012 0.034

Prechorus Refrain Solo Strophe Verse

Bridge 0.027 0.031 0.063 0.012 0.082 Chorus 0.099 0.038 0.041 0.030 0.158 Interlude 0.099 0.039 0.048 0.036 0.192 Intro 0.005 0.002 0 0.007 0.084 Outro 0.033 0.022 0.038 0.008 0.049 Postchorus 0.047 0.029 0.064 0.017 0.151 Prechorus 0.210 0.036 0.044 0.029 0.184 Refrain 0.058 0.038 0.026 0.051 0.314 Solo 0.054 0.027 0.076 0.022 0.125 Strophe 0.043 0.012 0.025 0.080 0.270 Verse 0.086 0.032 0.015 0.048 0.438

Figure 4.4. Transition probabilities by form in the Function corpus (n = 433 songs).

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Style and Performance Practice in the Function Corpus

The following section outlines how data in the Function corpus supports the

Parsimony, Harmony, Form and Transition performance practice principles outlined in chapter 3. As shown, rhythm guitar tracks in the Function corpus again demonstrate that performers generally prefer to move as a little as possible within fretboard space and reserve larger transitions for formal boundaries. Harmony, as a byproduct of fretboard parsimony, is meanwhile stylistically distinct: rock music in the Function corpus parallels that of the Modal-

Pentatonic corpus, while pop music is perhaps closer to theorist intuitions about Western

European common-practice music. Timbre also likely plays a role in the characteristic harmonic patterns of rock and pop music, as the lack of overdrive in pop potentially permits more-frequent use of major thirds than in rock music.

Parsimony and Harmony: Harmonic Patterning

Figure 4.5 demonstrates the proportional distribution of bass-note harmonic transitions taken from randomly sampled guitar tracks (n = 200) in the Function corpus.

These tracks divide evenly into pop (n = 100) and rock (n = 100) styles as labels provided not by me but by the users of ultimate-guitar.com. Like before, I assume that these note-to-note

(i.e., “salami-sliced”) bass note transitional values generally reflect harmonic root motion, given previously cited evidence that approximately 90% of harmonies in the Rolling Stone and

Billboard corpora are in root position. Figure 4.5 sorts the proportion of pitch transitions in the Function corpus by style, where the dark bars indicate the overall proportion (out of 1) for songs in a pop style, and the lighter bars indicate the same for rock songs.

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Overall, rock songs (n = 26202 note transitions) demonstrate a propensity for harmonic transition by major second (ascending, n = 2864; descending, n = 2807), followed closely by ascending minor third (n = 2215) and descending fourth (n = 2193). Pop songs contrastingly move primarily by ascending fifth (n = 2176) but share rock’s priority for descending fourth (n = 2112) and ascending second (n = 2029). But where these values become interesting is in cross-style comparison.

Figure 4.5 illustrates this most clearly, where rock’s priority toward motion by second dwarfs all other types of harmonic transition. Pop songs are meanwhile perhaps more balanced, with ascending major seconds, ascending fourths, ascending fifths and descending fourths all falling within ~9% of the total types of bass-pitch transitions. If these values are taken as indicative of the stylistic differences between rock and pop music, at least from a performative standpoint, a few notable trends emerge.

First, rock music in the Function corpus is dominated by stepwise (major second) transitions, both ascending and descending. Again, this supports the observations of

Stephenson (2002) and Biamonte (2011), who both give due emphasis to root motion by second. Stephenson is slightly off mark, in that rock songs feature proportionally more ascending seconds than descending seconds, putting rock closer to his proposed model of common-practice music. However, the data again encouragingly supports Biamonte’s modal perspective on rock through stepwise root-motion patterns (e.g., the Aeolian progression)

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Figure 4.5. Pitch transitions by style in the Function corpus

116 due in part to the over-abundance of ascending and descending major seconds, ascending minor thirds, and descending fourths. These most-frequent transitions also track with the findings of chapter 3’s analysis of the Biamonte Modal-Pentatonic corpus, which reports similar performative and harmonic transitions. By this measure, the “rock” music of the

Modal-Pentatonic corpus is indeed similar to the “rock” music of the historically and stylistically expansive Function corpus.

Second, the data also provide insight into what harmonic transitions constitute

“pop” guitar performance and, by extension, “pop” harmonic syntax. Here is where comparison between styles proves valuable. Specifically, instances where pop “beats” rock in terms of proportional bass-pitch motion reveal that its harmonic transitions are inversional, meaning pop songs use proportionally more ascending and descending major thirds, perfect fourths, and perfect fifths than rock songs. Because the frequency of pop’s interval transitions are also more balanced overall (i.e., no one of the top-four pop interval transitions dominates another), this perhaps suggest that harmonic practice in pop songs is less stylistically constrained. That is, unlike the rock songs in the Function and Modal-Pentatonic corpus, there is no one clear underlying harmonic system, such as the minor pentatonic scale.

Finally, assessing the Euclidean distances associated with the top-four most-frequent pitch transitions between styles reveals that rock guitar performance is less parsimonious

(mean = 1.81 frets) than in a pop style (mean = 1.56). Nevertheless, both styles still maintain noticeable parsimony in their respective fretboard profiles and, perhaps unsurprisingly, the top-eight most-frequent pitch transitions between pop and rock produce the same exact fretboard diagram produced by the Modal-Pentatonic corpus (Figure 3.19). Where the styles 117 differ is in what intervals they prioritize. Figure 4.6 plots all intervals that make up 5% or more of note transitions from the sample on an abstract fretboard, highlighting in grey intervals prioritized more in pop and in white intervals prioritized more in rock.52

Fret

3 4 5 7 -2 -1 2 1 2 -7 -5 -4 -3

Figure 4.6. Top 5% of harmonic transitions in the Function corpus sample (n = 200 songs) modeled on an abstract fretboard by fret distance. Grey nodes represent instances where transitions occur proportionally more frequently in a pop style than in a rock style. White nodes represent the reverse.

Speculating further on performative concerns, it seems as if rock guitar performance focuses more on the horizontal vector of the fretboard. This occurs anecdotally in the examples provided in chapter 3, where Dave Davies for example traverses the entire octave from F2 to F3 horizontally. The data, however, also suggest this stylistic difference due to the abundance and overt use of major ascending and descending seconds in rock—an

52 In both pop and rock styles, intervals of more than a fifth, ascending or descending, occur at a rate of 3% or less throughout the corpus.

118 interval that, unlike the minor third, cannot be easily executed in both the horizontal and vertical domain.

I hesitate to generalize further about any implicit tonal system inferred from Figure

4.6, other than pop music tends to orient itself toward major thirds (both ascending and descending) whereas rock employs more minor-third transitions. I hesitate because this information does not necessarily mean that pop music is somehow more “major sounding” than rock. It does also not imply that rock uses more “flat-side” harmonies than pop, as the black dot in the center of Figure 4.6 simply provides an arbitrary position from which to measure performative and harmonic distance. This dot is not presumed to be the tonic or tonal center of a passage. Even if this center were considered to be a tonal center, the flat- side argument still falls short, as pop music’s transition down a major third results in a flat- six or lowered submediant harmony. I also agree with Biamonte’s claim that not all popular- music textures consist of tertian harmonies, especially when guitars are involved (2010, 95).53

Finally, it again seems that timbre and harmonic dissonance contribute to the differences between rock and pop’s harmonic syntax in the Function corpus.

Though I do not have the concrete empirical evidence to support this claim, I would argue most of the “pop” songs in the function corpus do not use overdrive in the guitar parts. That is, the guitar parts in a pop style use a “clean” (i.e., non-distorted) tone setting.

Because of this, there are potentially less dissonances introduced when playing intervals of a major third, as the fifth of the destination note does not conflict with the fundamental of the

53 This claim warrants further testing on the corpus’s MIDI files using Humdrum’s hint (harmonic interval) command. White 2013 also finds that many of the harmonic verticalities in common-practice music are not triads at all, but are rather often dyads or non-consonant intervals such as perfect fourths. 119 previous pitch. The same argument can be made for the use of fifth-based progressions— that the overtone of the fifth (a major ninth) is less audible and therefore more consonant with the previous note’s fundamental.

Formal Characteristics

The relationship between form and pitch in the Function corpus contrasts from that of the Modal-Pentatonic corpus most starkly by style category. Figure 4.7 highlights how, even by form, the rock songs in the Function corpus and songs from the Modal-Pentatonic corpus quite similar by measures of harmonic transition. Again obvious is the overuse of ascending and descending major seconds, as well as minor thirds. The most curious difference between the two is the Function corpus’s introduction of ascending and descending minor seconds, of which the Modal-Pentatonic corpus has comparatively few. I suspect their newfound representation in the former is due to the classification and inclusion of heavy metal or alternative songs such as “Mummy Dust” by Ghost or “Ties That Bind” by Alter Bridge.

The chorus of “Ties That Bind,” for example, features a repeated F (1, 1) to E (0, 1) root- motion transition.

In terms of formal transitions, changes in pitch and physical distance in the Function corpus hold a similar predictive relationship to formal organization to that of the Modal-

Pentatonic corpus. I again use a mixed linear effects model to determine if pitch distance and

Euclidean distance can predict shifts in musical form, while also accounting for notable metric gaps between pitch transitions. First, a correlation test to evaluate co-linearity between the two variables and suggests that there is not a linear relationship between

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Euclidean and pitch distance (r (10544) = .025, p < .001). Proceeding with the model in

Figure 4.8, the results suggests that there is a significant relationship between Euclidean distance and form and pitch distance and form (binomial glmer, n = 105,493 transitions;

Euclidean distance, p < .001; pitch distance, p < .001).

Modal-

Pop Rock Pentatonic Module type Module Most frequent types of pitch transitions Secondary verse 5, 7, -5 2, -3, 2 2, -2, 3 Primary chorus 2, 7, 5 2, -2, -1 2, -2, 3 Auxiliary intro 2, -5, 5 2, -2, 3 2, -2, 3 Auxiliary outro 5, 2, -5 2, -2, 5 2, -2, 5 Primary refrain -5, -2, -9 5, -2, 3 -2, 2, 3 Auxiliary interlude 2, -2, 5 -2, 2, 1 2, -1, 7 Primary strophe 3, 7, 5 3, 2, -3 2, 3, -5 Secondary prechorus -2, 2, 5 3, 2, 5 2, -3, -7 Secondary postchorus 2, -4, -5 2, 3, 1 2, -2, -3 Secondary bridge 7, -5, 2 2, 1, -2 2, 3, -2

Figure 4.7. Most frequent types of bass-pitch transitions by style in the Function and Modal- Pentatonic corpora.

Unlike the Modal-Pentatonic corpus model, this model shows a slightly more meaningful positive effect between Euclidean distance and formal transition (r = .221) in the

Function corpus, while the previous negative relationship between pitch distance and formal transition diminishes further (r = -.025). I find these results encouraging, despite the still 121 relatively small effect, specifically because it illustrates in a larger and more stylistically diverse sample that performative transitions on an instrument potentially have greater bearing on formal organization and segmentation than pitch data, which tracks with the standing hypothesis about the syntactic nature of pitch and harmony in popular music.

Mixed-Effects Model Estimate Std. Error z-value P-value Intercept -3.458 .590 -5.825 < .001 Euclidean .221 .009 23.064 <.001 Pitch -.025 .003 -8.408 <.001

Random Effects Variance Std. Dev. Gap 1.781 1.335

Figure 4.8. Generalized linear mixed-effects model to predict moments of formal transition via Euclidean and pitch distance, with the random variable of a metric gap between notes in the Function corpus.

Discussion

With the data provided by the Features and Function corpus, I provide a clearer approximation of the surface-level stylistic-functional components of popular music and how these components influence socially determined measures of pop and rock as styles themselves. Previous to this study, music theorists primarily employed reductive approaches to popular music, presumably due to constraints associated with transcription and data categorization (i.e., collating surface-level features into a manageable format).54 In parsing

54 See de Clercq’s response to Gauvin (2015), where de Clercq advocates for a unified method of encoding for form and harmony in popular music corpus studies (243). 122 tablature to infer pitch information in the context for form, I offer evidence that suggests music in a pop style is categorically distinct from the rock songs of the “classic rock” cannon often studied by music theorists such as Biamonte (2010), Everett (2008), Temperley (2011), de Clercq (2017), and Nobile (2017).

Limitations of my current approach are also apparent. In particular, the “salami- slice” method I adapt from Quinn 2010 (and subsequently White 2013) might in fact be too fine-grained. Even though I intentionally give focus to guitar parts that fall best under a rhythm guitar label, single-note melodic lines are unavoidable. This is less problematic when these lines act as riffs, or repeated melodic patterns that shape the rhythmic and harmonic profile of the song, but occasionally songs and parts use non-thematic melodic lines as transitory material from one section to another, thus diffusing assessments of changes in physical transitions across forms, as well as inflating harmonic transition values. In addition to these concerns, as the rich scholarship on meter in rock suggests (Biamonte 2014, Osborn

2014, Temperley 2011), there is a critical relationship between meter, harmony and form. In future work, in response to both of these issues, it seems pertinent to parse the corpus with a moderate level of reduction—perhaps by limiting observations to quarter-note pulses, again following Quinn (2010).

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5. Chapter 5: Affordant Pressures on Guitar Performance Practice

In chapter 3, I present evidence to suggest that harmonic grammar and formal

function in modal rock songs share a close relationship with fretboard affordances.

Specifically, I demonstrate that note-to-note harmonic transitions are executed in a

comparatively narrow range on the fretboard (~1–1.8 frets) and evoke a minor pentatonic

collection. I also demonstrate that larger gestures in fretboard space occur most frequently at

moments of formal transition, so much so that larger transitions in fretboard space

statistically predict changes in form.

Chapter 4 corroborates these findings in the Pop-rock Function corpus—an expanded

and stylistically, historically and socially diverse corpus of pop and rock songs. There, I

speculate that the overuse of major seconds in rock music indicates that performers

demonstrate increased mobility in the horizontal (i.e., along-string) vector of the fretboard

when performing in a rock style, whereas pop performance potentially focuses more on

vertical (i.e., cross-string) transitions. Rock guitar performance again also subscribes

primarily to a minor pentatonic harmonic grammar, whereas pop guitar performance is

perhaps more diatonic (i.e., evokes a major-minor or Ionian-Aeolian tonal system). My

theory of formal function in the Modal-Pentatonic corpus is similarly convincing in the Function

corpus but is potentially weakened due to differences in riff-based and chord-based guitar

textures, as well as increased fluidity between mediating formal sections (i.e., prechorus to

chorus) through single-note melodic transitions.

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Regardless of the encouraging results, there are various methodological caveats to consider. Tablature, despite its computational utility, is not necessarily reflective of general performance practice. That is, it may be the case that tablature represents an idealized interpretation of musical structure—one not subject to the pressures of real-time performance. Similarly, even though the tablature from the Modal-Pentatonic and Function corpora are validated for quality by the ultimate-guitar.com community, the transcriptions are still just one possible model. Given the extensive permutations of note choice afforded by the harmonic recursivity of fretboard space, it is likely the original performer-composer executes the texture in another way and perhaps differently across performances.

Difference in style also pervade. In the Modal-Pentatonic corpus, a handful of songs are qualified as “pop” and/or “pop-rock” by the ultimate-guitar.com community, even though

Biamonte and I ascribe them as rock. Pop songs, in particular, are generally more parsimonious in fretboard space (mean Euclidean distance = 1.56 frets) than rock (mean =

1.81 frets). Some of these differences are explained by distinctions in harmonic grammar

(i.e., minor pentatonic vs. major-minor), but it is not clear to what extent they extend to real- time performance.

Finally, the distance metric I employ in the corpus study is based on a Cartesian idealization of the guitar fretboard. That is, it is a theoretical model that treats distances between frets and strings as equal. However, this is not the case with real guitar fretboards, where the x-axis features increasingly smaller fret sizes as the performer moves up the neck toward the body of the instrument. Similarly, cross-string distances are not equivalent to along-string (fret-to-fret) distances. On a real fretboard, the space between strings is

125 assuredly smaller than fret-to-fret transitions, perhaps beside the highest range of the fretboard where frets are smallest.

To summarize, the performance practice results from the Modal-Pentatonic and Function corpora present the following complications or caveats:

1. Tablature is not necessarily reflective of actual performance practice.

2. Tablature represents one interpretation of how to execute musical structure, even if it has been validated by others.

3. Tablature is not enacted in real time.

4. There is no accounting for differences in riff- versus chord-based harmonic progressions.

5. Even in the Modal-Pentatonic corpus, ultimate-guitar.com metadata (users) qualify some songs as “pop,” in conflict with Biamonte’s assessment. Pop and rock songs demonstrate differences in performative tendencies.

6. Transitions between forms are assessed on a note-to-note basis, even though melodic fills may intermediate otherwise large shifts in distance.

7. Along-string and cross-string transitional distances on a real guitar fretboard do not reflect those suggested by the theoretical model used in chapters 3 and 4.

Each of these concerns suggest a need for cross-validation in real-time performances by human musicians. In this chapter, I investigate how performers execute musical structure in real time, based on a pre-existing and style-dependent harmonic progression.

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Study: Motion-Capture and Style

Hypotheses

This study evaluates how the harmonic-physical structure of instruments, style, and tempo act as pressures on their generation of musical texture. The following hypotheses assess how theoretical concepts such as formal and harmonic function intersect with these concerns, under an ecological model of affordances.

H1. Formal function. Performers will situate the largest performative gestures at hypermetric (e.g., every four chords) and formal (e.g., every eight chords) transitions, regardless of genre or tempo, assuming a consistent harmonic rhythm. H2. Harmonic function. Performers will execute larger gestures in the third-based progression than in the fourth-based progression, due to the affordances and tuning of the electric guitar. H3. Tempo. Performers will perform a greater proportion of larger gestures at a slower tempo (90 bpm) than a faster one (120 bpm), due to Fitts’s Law.

Each condition of the experiment (e.g., pop or rock, tempo) addresses these facets of performance practice.

Materials

The motion capture rig in Figure 5.1 consists of a 1) a 2009 Squire Affinity “Strat” guitar, which is typically bundled with the “Squire Strat Pack” sold by Fender, 2) a 48-inch

(length) by 3/4-inch (width) flat aluminum bar, 3) a USB-powered (2.1 volts) 1/2-inch strip of adhesive LED lights, 4) a portable USB charger, 5) a Yi 4k Action Camera, 6) a tripod mount, 7) a roll of pink-colored low-stick athletic tape, 8) and fastening components that

127 include 5 Phillips-head bolts with washers, an aluminum four-hole “L” bracket, and three threaded inserts for woodworking. The total cost for these materials is less than $350 USD.

Figure 5.1. Motion-capture rig, materials and cost.

To position the camera above the fretboard, the aluminum bar is bent and cut to provide a stable platform on which the camera rests.55 The largest aluminum piece extends from the headstock to the body of the guitar, just above the pickguard and middle pickup. A second smaller aluminum piece provides structural integrity for the larger one and is positioned between the body’s upper-register fretboard cutaway and the pickup switch.

55The rig was assembled in collaboration with Oded Huberman, Interdisciplinary Production Manager at the Ohio State Department of Dance and the Advanced Computing Center for the Arts and Design. Many thanks to Oded for his creative approach to the project’s unique methodological challenges. 128

These pieces of the rig are bolted to the headstock and body of the guitar, first by drilling a pilot hole for the threaded inserts into the guitar, then by drilling a hole into the aluminum itself. Bolts then pass through the aluminum into the inserts to secure the rigging to the body. The larger aluminum piece is slightly curved. At its highest point it is approximately eight inches away from the fretboard, above the sixth fret. This is where the “L” bracket is fastened to the aluminum via a bolt and washer. The Yi Action camera attaches to the “L” bracket using the tripod mount. Once the aluminum rigging is in place, the LED lights attach to the underside to illuminate the fretboard. The USB port feeds into the battery pack, which attaches to the back of the guitar via adhesive.

To test hypotheses related to style and genre, performers play the chord progression in Figure 5.2. The chord progression is specifically balanced around competing types of root motion (i.e., third-based versus fourth-based), and is meant to reflect research intuitions about harmonic differences in style demonstrated in the root motion transitions in chapter 2.

The chord progression features eight transitions by perfect fourth/fifth and eight transitions by major/minor third/sixth. The first seven chord transitions evoke the “rock” genre through the use of the “double authentic” progression featured in fretboard-idiomatic songs such as “What I Like About You” by The Romantics or “Cherry Cherry” by Neil Diamond.

The latter seven transitions are meanwhile third-based and, though the pattern does not subscribe to any typical stock harmonic progression, it reflects the third-like nature of pop harmony illustrated in chapter 4.

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Figure 5.2. Symmetrical chord progression used in all conditions.

Method: Motion Capture

The motion capture process involves tracking the position a guitarist’s left hand as they play a chord progression. Performers attach a pink strip of athletic tape to the middle digit of their left index finger and a program I built in Max MSP calculates the relative position of the color pink on a frame-by-frame basis from the footage recorded by the Yi

Action camera.56

Distance is calculated using the Euclidean distance formula. Distance is measured by pixels—the number of which is contingent on the camera’s resolution. For this study, the Yi

Action camera’s resolution is set to 1080x1920 on the “Wide” field-of-view setting at a rate of 60 frames per second. The camera’s field of view is adjusted so it encompasses the nut to the fourteenth fret. Figure 5.3 demonstrates the camera’s scope.

56 Note: in for this process to work correctly, the performer cannot be wearing the color pink and there cannot be any pink objects in the background.

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relative position of hand pink tape in performance space A. B.

Figure 5.3. Performer left hand with pink tape on index finger (A) and motion-capture frame (B). The box tracks the color pink to approximate hand centering and reports coordinates.

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The distance-tracking program specifically calculates distance by estimating the boundaries of the pink tape on the screen. The boundary is represented as two points which are visualized as opposite corners of a square. The midpoint of the square approximates the central position of the finger and, by extension, the hand. Each data point is encoded in a

Cartesian coordinate format. For example, in a resolution of 1080 (height) by 1920 (width) pixels, when a performer’s index finger is situated exactly at the midpoint of the screen, the program reports the Cartesian coordinates as (540, 960). If the performer then moves their hand down in height and slightly to the left to (360, 640), the distance moved totals ~367 pixels.

Participants

All participants in this study are members of local performance communities in

Columbus, OH. I intentionally excluded Ohio State music majors, as I specifically seek to evaluate musical understanding in semi-professional musicians. I recruited participants primarily through a Reddit post and flyers posted at a local coffee shop. All participants were paid a minimum of $10 regardless of participation length, then at a rate of $10 per hour after the first hour.

Method: Performance and Recording

Performers play the given chord progression in a soundproof booth wearing

Sennheiser HD 280 Pro headphones. The headphones and guitar connect to a Lexicon

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Lambda external USB mixer, which acts as an audio interface for the Apple program Garage

Band. I encourage performers to adjust the audio levels to their liking.57 After doing so, I ask performers if they are ready to begin and presented with the following prompt:

Imagine you are a studio musician and have been asked to perform the harmonies for a song written by two popular-music artists; a rock musician and a top-40 pop musician. Your job is to realize the given chord progression on your instrument that reflects these rock or pop styles. You will also be asked to perform the songs at two different tempos. The researcher will notify you in which style and tempo you should perform before you begin. Overall, your progression will serve as the foundation for the entire song (a.k.a., the backing track), so aim for a relatively simple texture that is easy to repeat as the chord progression loops. Please take some time to practice your chord progression. Once you are ready, notify the researcher and we will begin recording your “final” versions. You will perform four takes in total—one for each style and tempo. The performers are then given the chord progression in the above Figure 5.2. The performers practice the given chord progression in coordination with a generic backbeat drumbeat, specifically developed in consultation with Daniel Shanahan to avoid any orientation toward either a pop or rock style. The beat presets and waveform are presented in Figure 5.4 below. The drumbeat does not change when played at different tempi.58

57 Due to possible demand characteristics due to timbre highlighted in the previous chapter, I do not allow participants to set the tone of model amp and instead leave it on a “clean” (i.e., no overdrive) setting. 58 Upon completing the performance task, participants complete the Goldsmiths Musical Sophistication Index, v1.0 survey via a browser-based Qualtrics survey. 133

Figure 5.4. Garage Band drumbeat presets and waveform used in the performance task.

Participants practice both styles for a minimum of 10 minutes under each tempo condition (i.e., 10 minutes to practice pop/rock at 90 bpm, 10 minutes to practice pop/rock at 120 bpm). After 10 minutes, I check in with participants to see if they are ready to record.

If they indicate they would like more time to practice, I offer them 5 more minutes, after which we record the track.

Performers record a total of four final takes, one for each condition of the experiment, in the following order: pop at 90 bpm, rock at 90 bpm, pop at 120 bpm and

134 rock at 120 bpm. 59 After each take, I ask if they find the take to be satisfactory and, if not, allow them to re-record the take. However, to reduce demand characteristics on the data analysis I use no more than the first three takes of each condition.60 That is, I select what I deem to be the best take out of the first three takes. Most sessions lasted 50 minutes and no longer than 90 minutes.

Cleaning the Data

During the motion-capture process, participants occasionally position their fingers outside of the boundaries of the screen. When this occurs, the motion-capture program assumes there is no data and thus reports a value of (-1, -1), which does not exist on the

1080x1920 pixel coordinate plane. This skews measures of Euclidean distance. Luckily the majority of these moments in the data are rare, occurring in less than approximately 300 millisecond spans. I accordingly parse such instances from the data with little consequence to the overall assessment of Euclidean distance.61 Participant 9, however, does consistently move their finger outside of the camera’s boundary (by sticking their index finger straight up over the approximate span of three chord transitions) in the pop/120 bpm condition. As such, I exclude their data from the following analyses in that experiment condition.

59 The style sequence is arbitrary, but I chose this specific tempo order under the assumption that performers might be more inclined to use the same performance pattern when moving from a faster to a slower tempo, but might be forced to employ a more efficient pattern if moving from a slower to faster pattern, thus approximating Fitts’s law. 60 I choose to do this because of an experience in the pilot study, where one participant was quite nervous during the first take. This also occurred in the current study. Allowing these guitarists to do further takes increased the quality of their recordings. However, I also understand that a series of many takes eventually equates to practicing, which is why I limit the analysis to the first three takes. 61 This process results in a loss of ~1000 frames or 50 seconds worth of footage across 52 separate takes, averaging ~1 second per take. 135

Coordinating gesture and hierarchical structure requires parsing chords, hypermeter, and form into discrete temporal units. I do so by listening to and watching each performance in Max MSP and tapping the spacebar upon the initiation of each chord. This inserts a marker into the frame-by-frame data to delineate one chord from the next. I then sort each chord collection into hypermetric and formal units. A hypermetric unit is qualified as the beginning of the first to the end of the fourth chord (e.g., one cycle of the verse or chorus), whereas a formal unit consists of eight chords from the beginning of the first to the end of the eighth (e.g., the entirety of a verse or chorus).

In the experiment’s pilot phase, I defined moments of hypermetric (e.g., every four chords) and formal (e.g., every eight chords) transition as 10 frames (.5 seconds) before and after every relevant chord transition. For example, hypermetric transitions occur between chord four and five, meaning the transition zone spans 500 milliseconds on either side of chord five’s onset. Even in the small sample of the pilot (n = 4 guitarists), this comparatively narrow band often resulted in a performer’s physical transition sitting just outside of the transition zone, presumably due to my own latency in marking the chord onset in real-time, but also potentially due to the limitations of my computer’s video processor. In this study, I respond by adjusting the transition window to be slightly larger (1.5 seconds or 1500 ms) and proportionally sit further to the left of the relevant chord onset. This means, given a chord onset, I consider a transition window to exist 1,125 ms before the onset and 375 ms after.

Finally, my choice of the color pink for motion-tracking proved problematic for accurate distance assessment. This is because the LED lights create a pink reflection off the red body of the guitar that is similar enough in hue to the tape that the program believes the

136 window is larger than it is. To correct this issue, I inserted a black-box image overlay on the bottom right of all 52 videos, thus masking the pink reflection and limiting the tracking window to the participants’ index fingers.62

Descriptive Statistics and General Observations

After cleaning, the motion-capture data consists of 303,485 frames of coordinate information across 52 separate performances by 14 participants. The average X, Y coordinate position for performances in a pop style occur at (351, 546), while rock performances sit closer to the center of the fretboard at (532, 578). The data also reflect the fact that the horizontal (along-string) vector of the motion-capture frame takes up more space (x-axis: 0–1,604 pixels) than the vertical (cross-string) vector (y-axis: 321–734 pixels).

Thus, performers have a greater range of motion on the along-string vector.

Figures 5.5, 5.6, 5.7 and 5.8 illustrate this tendency across the experiment’s four conditions. These graphs are slightly misleading, in that the higher values on the graphs’ y axes actually reflect performances that are higher on the guitar’s x axis (i.e., fret positions closer to the body of the guitar). For example, in Figure 5.5 (pop style, 90 bpm), participant

2 plays the entire excerpt much higher on the neck than the majority of participants and largely remains in that area of the fretboard. From these graphs, it is clear that the majority of participants prefer to play progressions closer to the headstock, in the lower register of the

62 Future iterations of this study will use a different color of tape.

137

Figure 5.5. X-axis transitions over time, pop 90 bpm.

138

Figure 5.6. X-axis transitions over time, rock 90 bpm.

139

Figure 5.7. X-axis transitions over time, pop 120 bpm.

140

Figure 5.8. X-axis transitions over time, rock 120 bpm.

141 fretboard’s x-axis. However, many more participants do use the range of the along-string vector in rock performance than in pop performance.

Increased performer mobility along the x axis in a rock style suggests there are stylistic differences between pop and rock by along-string motion. But are there noticeable differences in style along the y axis? Figures 5.9, 5.10, 5.11, and 5.12 plot the density of y-axis transitions across each condition. These density plots indicate the frequency at which performers position their hand along the vertical axis of the fretboard. Unlike the previous graphs, I have flipped these graphs to reflect their y-axis orientation, where the coordinates on the left correspond to the image the motion-capture camera sees. As such, ~400 on the y axis approximates the position of the performer’s hand when they play the E string, while

~700 aligns when playing the high E string. These values, however, are not necessarily reflective of the actual string being played, as performers attach the strip of pink tape to their middle digit of their index finger, meaning that when a performer plays G on the low E string (3, 1) with their index finger, the program “sees” their finger position as slightly higher, on either the A or D string. As such, the position of the actual E string is actually at

~300 pixels on the x axis.

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Figure 5.9. Y-axis transitions density, pop 90 bpm.

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Figure 5.10. Y-axis transitions density, rock 90 bpm.

144

Figure 5.11. Y-axis transitions density, pop 120 bpm.

145

Figure 5.12. Y-axis transitions density, rock 120 bpm.

The graphs listed above demonstrate that performances in the pop condition tend to bifurcate between the upper and lower ranges of the along-string axis. That is, performers generally prefer a comparatively narrow band in the upper register (~620-pixel y-axis range) or mid-to-lower register (~480 y-axis range). Rock performances meanwhile center mostly around the ~600 y-axis pixel-coordinate range, especially in the slower (90 bpm) condition.

It is not clear why this is the case, but I suspect it relates to the theory suggested in chapter 4

146 and shown in Figures 5.9 and 5.11—that guitar performance in a pop style is more parsimonious in the cross-string (y-axis) vector than in the along-string vector.

Results

Test 1: Formal Function

I evaluate the relationship between Euclidean distance and form in a manner similar to previous chapters by determining if moments of hypermetric and formal transition are pronounced enough to mark or predict statistically changes in hypermeter or form. This method aligns with the Parsimony, Form and Transition principles from chapter 3, which suggest that intra-formal transitions are comparatively constrained to inter-formal transitions. Like previous chapters, I also use the same model, albeit a slightly simpler one, and account for a subject’s preferences instead of the presence of a metrical gap (as there are none):

Hypermetric transitions ~ Euclidean distance + (1 | subject) Formal transitions ~ Euclidean distance + (1 | subject)

This model applies across all 52 performances in each condition, as I assume that such transitions occur consistently across hypermetric and formal boundaries. However, I also predict that formal transitions will be more pronounced than hypermetric ones, hence the need for two separate tests.

The results of the model in Figure 5.13 indeed suggest that there is a significant relationship between Euclidean distance and hypermetric and formal organization (binomial

147 glme, n = 303,485 transitions). Both variables have a small but positive effect on hypermetric transition (hypermeter Euclidean, r = .009) and formal transition (form

Euclidean, r = .008). However, because the effect size is so small despite the large sample size, I regard the results skeptically and believe there is room for further testing by style and tempo in future work.

Hypermeter GLME Estimate Std. Error z-value P-value Intercept -2.274 .016 -136.01 < .001 Euclidean .009 <.001 21.02 <.001

Random Effects Variance Std. Dev. Subject .003 .058

Form GLME Estimate Std. Error z-value P-value Intercept -3.177 .016 -196.18 < .001 Euclidean .008 <.001 16.01 <.001

Random Effects Variance Std. Dev. Gap .002 .049

Figure 5.13. Generalized linear mixed-effects models for hypermetric and formal transitions.

Test 2: Harmonic Function

I expect third-based progressions to be more difficult to execute than fourth-based ones, due simply to the guitar’s tuning by perfect fourth, with Euclidean distance values acting as an assessment of difficulty. Evidence of this occurs indirectly when comparing the average performative distances between the major-second/minor-third driven rock songs 148 and perfect-fifth/major-third driven pop songs in the Function corpus (rock = 1.81 frets, pop

= 1.56 frets). However, the chord progression that participants play from operates on a slightly different premise—that the fourth-based “verse” aligns more with a rock style and is easier to play than the third-based “chorus” that reflects a pop style. Figure 5.14 and 5.15 respectively report the density or distribution of Euclidean distance across the rock (mean =

2.168 pixels) and pop (mean = 2.56 pixels) conditions. As shown, the data are not normally distributed around a mean (i.e., average) value and in both groups approximately 30% of distance values are at zero.

Because of the non-normally distributed data, I first remove all zero values, as my goal is to assess moments of transition and not moments of rest. Figure 5.16 reports the new distribution with a box-and-whisker plot by progression type. Next, I employ the Two- sample Wilcoxon rank-sum (Mann-Whitney) test. This test is analogous to a two-sample t- test, which compares the means of the dependent variable (Euclidean distance) between two independent variables. The test suggests there is a significant difference in Euclidean distance between the fourth-based chorus and the third-based verse (p < .001).63 That is, the data are consistent with the hypothesis that there is a meaningful difference in transition values between harmonic progression types.

63 The formula [wilcox.test(euc.dist ~ form, data = test.H2)] reports p-value = 4.173e-09. 149

Figure 5.14. Density of Euclidean distance, fourth-based progression.

Figure 5.15. Density of Euclidean distance, third-based progression.

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Figure 5.16. Box plot of Euclidean distance by progression type.

Test 3: Fitts’s Law

Fitts’s law, simply stated, posits that performance accuracy is contingent on distance and speed. In chapter 3 and 4, I indirectly consider Fitts’s law by accounting for prolonged gaps or moments of silence in a song’s metrical framework when testing the relationship between form and Euclidean distance in the Function corpus. Those tests evaluate distance as a factor of Fitts’s law, while the following test considers the role of performance speed.64 I

64 Note that I do not explicitly address accuracy as a factor of Fitts’s law in this document. This is an avenue for future work. 151 specifically test the third hypothesis—that performers use smaller distances at faster tempi— using a similar methodology as before by separating the data into two conditions: slower (90 bpm) and moderate (120 bpm). An initial comparison of means suggests greater promise of a meaningful difference between songs at 90 bpm (mean = 134.986 pixels) and 120 bpm

(mean = 76.744 pixels). Figure 5.17 shows the distribution of these variables on a box-and- whisker plot after removing non-transition (zero) values. The Wilcoxon test reports a significant difference in Euclidean distance between songs at 90 and 120 bpm (p < .001).65

Figure 5.17. Box plot of Euclidean distance by bpm.

65 The formula [wilcox.test(euc.dist ~ BPM, data = test.H3)] reports a p-value of < 2.2e-16. 152

Discussion

In future iterations of motion-capture work, I intend to also assess how a participant’s experience influences performance practice decisions. I did ask participants to take the Goldsmith’s Musical Sophistication Index 2.0 which reports, among other things, a performer’s range of musical experience and their preferences for specific styles such as pop, rock, jazz or classical music. Even though this data are not considered at present, I do suspect experience plays an important role in performance execution. For example, Figures

5.5 and 5.6 show in both pop conditions that many of the performers chose to voice their chords nearest to the headstock using open-string chords. But rather than suggesting that these participants lack experience overall, they may rather lack experience in a specific style.

Participant 6 exemplifies this trend. As a singer-songwriter who primarily performers from the piano, she recounted that she recently decided to take up guitar and saw my flyer in a local coffee shop. Perhaps unsurprisingly, her performance was constrained to a narrow range on the fretboard and played the chords for each condition in the same position.

However, her performance also revealed a critical distinction of style not considered by this study: she employed rhythm instead register by electing to use a syncopated pattern for the rock conditions and a more isochronous one for pop. Similar evidence across other participants and my analysis of corpora lead me to believe that rhythm is an important indicator of style, especially for less experienced players.

Another indication of style outside the reach of this study is the difference between chord voicings. At least four participants asked me something to the effect of “So I should play this [the pop condition] in a more open style, right?” To which I always responded, “It’s

153 up to you.” But I also suspect that, at a certain level of experience, these concerns matter less. Participant 5, for example, gave arguably the most expert performance of all, especially in the rock conditions. He has a total of 15 years’ worth of experience playing blues and classical guitar. Resultingly, I would describe his choice of voicings as incredibly efficient and evocative of the blues guitar style made famous by Keith Richards, guitarist for the Rolling

Stones. In the study debrief, he remarked on timbre, not harmony, as the inspiration behind his performance, point toward the suitability of the guitar’s tone for rock and noting that the clean setting was “just right.” Both of these concerns—experience and chord voicing— perhaps contribute to the bifurcation of pop performances along the y-axis. That is, anecdotally it seems performers with less experience preferred to play open-string voicings in the low register of the fretboard, near the headstock, while those with more experience presumably explored the upper registers of both the x and y axes. In sum, less experienced players might fall within the bottom peak of Figure 5.9 and 5.10.

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6. Chapter 6: Dissonance Treatment and Performance Practice

in “Paris is Burning” by St. Vincent

Empirical studies, when properly designed, offer remarkable explanatory power about general compositional convention. In the previous chapters, I suggest through corpora and motion-capture analysis that the five principles of guitar performance practice offered in chapter 3 consistently apply to facsimiles of popular-music songs and in the real-time performances of stylistically characteristic chord progressions by practicing guitarists. Data from these contexts demonstrate that guitarists most often execute popular music’s common-stock harmonic progressions in a parsimonious or stepwise manner, where movement by perfect fourth or major second constitutes a step in fretboard space, thus supporting the proposed Harmony and Parsimony principles. Each test on the corpus and motion-capture data also highlights the explicit relationship between gesture and form outlined in the Form and Transition principles; namely that performers consistently use larger gestures across changes in formal and hypermetric cycles. While these changes in form may be audible to listeners due to overt shifts in texture and timbre, the data cross validate that performance practice also presents a reliable assessment of formal function and segmentation.

My computational analyses also reveal practical differences between songs that fall under a socially determined style of either rock or pop. For example, rock guitar performance tends to be less performatively parsimonious and uses along-string harmonic transitions, in opposition to pop songs which are more constrained and more often feature 155 harmonic shifts in the cross-string domain. This coincides with notable differences in characteristic bass-note transitions across styles, where rock guitar’s harmonic syntax consists primarily of transitions by ascending/descending major/minor second and ascending/descending minor thirds. Pop harmony meanwhile more often employs shifts by ascending/descending major thirds and ascending/descending perfect fifths. Such differences may be the result of timbre and harmonic dissonance, as pop songs are less likely to use overdrive, which heightens the audibility of a note’s overtones.

Despite the value of these findings for establishing a basis of style and performance practice in popular music, empirical methods do not always suffice when investigating instances of ambiguity and nuance in an individual work. This is especially true of contemporary guitar performance, where the stylistic boundaries between pop and rock styles are often unclear. Documented obstacles in popular-music analysis compound these concerns, such as the melodic-harmonic divorce (Temperley 2007; Nobile 2015), the innate ambiguity of short harmonic loops (Richards 2017) and the presence of competing modal- pentatonic tonal systems (Biamonte 2010). To address similar issues in chapter 3’s analysis of

“Hey Jude,” I highlight how Paul McCartney’s navigation of fretboard space accounts for the passage’s use of a secondary dominant, thus supporting de Clercq’s hearing of the passage in a (local) B-flat key center. A close (but short) reading, in this context, helps to address an instance of musical ambiguity.

In the following section, I embark on a longer close reading of the song “Paris is

Burning” by Annie Clark, the artist known as St. Vincent, to address its key moments of ambiguity and function. As I highlight in the analysis, this contemporary work features

156 variety of stylistic components from rock, pop and common-practice music, the latter of which I surmise develops from Clark’s training at the Berklee College of Music. My overall goal with the analysis is to articulate how Clark’s performance decisions in fretboard space contribute to the stylistic aesthetic of “Paris is Burning,” how her performance maintains the outlined principles of parsimony, form and formal function, and how adherence to these principles creates moments of ambiguity such as the melodic-harmonic divorce in the song’s verse. I also offer thoughts on how timbre influences dissonance and voice-leading in both pitch and instrument space.

My primary justification of a performance-based approach to “Paris is Burning” comes from a recent interview, where Clark describes the act of composition as a synthesis of her training, auditory preferences and her interaction with her guitar:

But I’m realizing now that – to be honest – music is a mystery to me. My own instincts, though I very much trust them now, are mysterious in their origin and ultimately I’m only ever trying to get at the sound that is there. And I’m going to try to bridge that gap between the theoretical and the actual.

I have this sound in my head. How do I get it here in my fingers? Then there’s the flip side of that, which is that the same way that the music is more mysterious to me than ever there are things that come out of my unconscious mind and my fingers that I couldn’t have imagined. They just exist and they’re there. And I go, ‘Oh that was cool!’ And so there’s always that – it’s nice to have a certain level of skill, but not so much that you can always presuppose the outcome. When I put my fingers down on the guitar I don’t know what it’s going to sound like and I’m somehow willfully ignorant in those microseconds.66

66 “St. Vincent: ‘I have this sound in my head. How do I get it here in my fingers?’” Salon Magazine, Moody 2014 (https://www.salon.com/2014/02/16/ st_vincent_i_have_this_sound_in_my_head_how_do_i_get_it_here_in_my_fingers/). 157

As Clark advocates, the following analysis draws upon both listener and performer perspectives on musical structure and, in response, I attempt to separate when possible

Clark’s various roles in the song’s performance. That is, I use a synthesis of pitch-based and performance analysis methods to respectively reflect her potential perspectives on the song’s structure as a listener and performer (vocalist and guitarist). Doing so encompasses the entire range of Temperley’s communicative pressure model, which I argue popular-music composers like Clark thoroughly inhabit in any live performance.

General Formal Organization and Tonal Frame

“Paris is Burning” is organized into three overarching sections: an introduction, the core module (verse, prechorus, chorus), and a texturally distinct and terminally climactic outro.67 In addition to its formal regularity, it is also hypermetrically stable, with the exception of the chorus which is proportionally double the length of the other modules.

Tonally, the song subscribes to all of the components of twentieth-century tonality as described by Harrison 2016 (10). These include use of counterpoint and voice leading, rhythm, vertical sonorities, and a normative harmonic syntax. To use Harrison’s metaphor of geography and tonal practice (41), if the common-practice period (ca. 1650–1850) is the topographical locus where linearity, meter, harmonic fluctuation, and tonal rhetoric converge to convey common-practice techniques, then the compositional choices employed by Clark

67 A terminally climactic form is one that is harmonically and texturally distinct from other formal zones and generates energy before interrupting a formal cycle or closing out a song. See “Subverting the Verse-Chorus Paradigm: Terminally Climactic Forms in Recent Rock Music” (Osborn 2013).

158 situate “Paris is Burning” in the ring suburb of Harmonic Fluctuation, squarely between the modern outskirts and the traditional city center. It is here where traditional models of counterpoint, harmony, and voice leading struggle to fully explicate the song’s inherent harmonic and functional ambiguities, therefore prompting analysts to consider alternative aural and embodied methodologies to model how listeners, performers, and composers as musical agents might understand its structures.

The Melodic-Harmonic Divorce

Annie Clark’s vocal line often seems at odds with the rest of the texture in the verse of “Paris is Burning.” The melody, transcribed in Figure 6.1, largely outlines the song’s tonal center of A-flat minor first established by the brass chorale in the introduction. This prolongation of A-flat, however, conflicts with the guitar part notated in the lower staff, which emphasizes B-flat as its tonal center. In addition to this harmonic conflict, the melody is also rhythmically fluid compared to the steady chordal arpeggiation in the guitar.

Figure 6.1. Transcription of Melody, guitar, and bass parts, verse, “Paris is Burning,” 0’ 18’’– 0’ 40’’

159

Even though music theorists have given much attention to similar instances of this melodic-harmonic “divorce” (Moore 1995, 189), I argue that a close analysis of Clark’s vocal and guitar parts from a performance perspective de-problematizes otherwise pertinent pitch- based analytical concerns. First, to make a case for each part’s respective tonal center, I draw on Harrison’s descriptions of overtonal systems.68 Critical to this is Harrison’s characterization of Schenker-lines (S-lines):

Like Schenkerian linear progressions, S-lines horizontalize an underlying tonality frame, with the beginning and end points of the line belonging to hierarchically important pitches in the local overtonal hierarchy (or, in a smaller scale, to notes of a local chord). Unlike linear progressions, each pitch in the line may or not be supported by its own chord, and even if chordal support is apparent, it may be more the product of independently moving lines, perhaps shaped with harmonic fluctuation, than of deliberate harmonic planing (83–84)

Based on this framework, Clark’s melody emphasizes A-flat specifically through the use of a double-neighbor motion around A-flat and by positioning its melodic peak and basement on

E-flat as the tonal center’s fifth scale degree. These pitches, as Harrison describes, are important members of the melody’s local overtonal hierarchy. Likewise, the general stepwise descent from E-flat and double-neighbor motion around E-flat conveys its curvilinearity, another feature of tonality and centricity, through directed stepwise motion in pitch space

(79–83).

68 I place such emphasis on establishing evidence for my choice of tonal center because I find other music theorists often take this decision for granted in popular-music analysis. For example, while de Clercq and Temperley (2011) admit that even in common-practice analysis that “harmonic analysis is somewhat subjective; two analysts (even using the same labelling system) will not necessarily analyse a piece in the same way” (54), they do not provide any concrete or standardized methodologies for how or why they might choose one tonal center over the other (regardless of whether or not the tonal center is global or local). I suspect that meter plays a large part in a listener’s decision, but research on this area of music perception is lacking. 160

The case for B-flat as the guitar part’s tonal center emerges through reduction in pitch class space. Figure 6.2 demonstrates that the top voice of each chord makes a smooth stepwise descent from B-flat all the way down to A-natural. In this figure, each quarter note represents an instantiation of a chord, while the bar line represents a complete progression through the four-chord cycle. On the final chord of the cycle, I argue this non-tertian sonority acts as a functional dominant of B-flat. Though not a dominant in the traditional sense, the A-natural, G-flat and E-flat converge on the diminished fifth and root of the B- flat chord through contrary and chromatic stepwise motion, effectively tonicizing the harmony. This is also the only point in which the progression through pitch-class space ascends instead of descends, from A-natural to B-flat.

Figure 6.2. Pitch-space reduction of voice leading in the guitar part starting from the root, verse, “Paris is Burning.” Each quarter note represents one chord in the verse’s harmonic cycle.

Harrison’s mention of “chordal support”—where he states that an S-line (the melody) need not be explicitly linked to its accompaniment to be considered reflective of an overarching tonal system—relates to Temperley’s (2007) conception of “loosely knit” and

161

“tightly knit” instances of the melodic-harmonic divorce. The former implies a greater degree of divorce and the latter indicates moments of congruence. Temperley and Nobile

(2014) typically use these terms to describe moments of harmonic alignment across forms

(e.g., Temperley’s loose verse/tight chorus model), but the loose/tight relationship in “Paris is Burning” occurs at a more local level within the phrase itself. Specifically, as the phrase progresses, it ebbs between a loose-knit and tight-knit organization.

This harmonic fluctuation occurs because the verse does feature moments of harmonic congruity—the shift from G-natural and G-flat in the melody coincides with the introduction of these tones in the guitar part. However, the G-flat interestingly serves a dual purpose depending on the part. In the guitar line, G-flat acts as an upper neighbor to the fifth of the B-flat tonal center, whereas its use in the melody is simply a neighbor motion using lowered scale-degree seven, which is commonplace in pop-rock melodies (as

Temperley 2007, Stephenson 2002, Biamonte 2010 and many other scholars illustrate).

Overall, it is this final chord of the four-chord loop that acts as a point of harmonic- functional divergence: even though the guitar part supports G-flat in the melody, the pitch takes on a separate functional role in each respective tonal center. Only at the previous chord, the E-flat major-minor chord, are the melody and harmony truly in alignment.

However, to use Harrison’s language, this moment of congruence seems to merely be the product of two independently moving lines shaped by harmonic fluctuation rather than deliberate harmonic planing. In this way, the apparent tight-knit organization is perhaps deceptive.

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Figure 6.3 provides a voice-leading reduction of the verse to highlight how its disparate harmonic structures relate under a unified tonal center. Note that this sketch is not meant to conform to or convey traditional Schenkerian techniques. That being said, while I follow Biamonte (2010) and Temperley (2004) in that I am generally resistant to Schenkerian principles in popular-music analysis, I do find that voice-leading graphs such as this one prove helpful in highlighting the relative structural importance of pitch relationships within a tonal center. That is, through note-head type, size and stemming, Figure 6.3 aims to highlight which pitches might be heard as more important to a listener in Harrison’s overtonal system.

Each staff (treble and bass) divides into two components—root motion (open note heads) and melodic voice-leading (typically on the top of the staff, upward stems). On a scale from most to least structural, open note heads occupy the highest level, followed by filled-in note heads with stems, stemless note heads, and finally un-stemmed small note heads. Slurs also link embellishing or less-structural tones to their prolonging tones, following the “stem and slur” method established by Forte and Gilbert (1982). As shown, A-flat and E-flat are the most prominent notes in the melody (voice), whereas the guitar and bass parts emphasize B- flat.

At this point there are two unresolved points of ambiguity: the harmonic independence between the melody and accompaniment and the functionally dominant but non-categorical and non-tertian harmony at the end of the four-chord cycle. To the latter, I provide evidence for the chord’s function from a listener’s (and perhaps a vocalist’s) perspective above, but it is still not clear how the guitar part aligns with the song’s global tonal system. Here is where I find value in a performance-practice approach.

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Figure 6.3. Voice-leading reduction of melody and guitar and bass parts, verse, “Paris is Burning,” 0’ 18’’ – 0’ 40’’

Approaching the harmonic idiosyncrasies of this progression from Clark’s perspective as a performer reveals that unified chord shapes and gestures within a designated instrument space are largely responsible for generating and articulating the verse’s tonal features. Figure 6.4 illustrates the lowest notes of the verse’s guitar part on a virtual fretboard using grey-colored nodes. Each node is numbered to indicate the chronological sequence of chords and below the fretboard diagram are groups of fret-string pairs that designate which notes are being articulated in a given chord. The arrangement of these chord shapes is centered on the fret of the chord’s lowest note. For example, the lowest note of the first chord of the verse is D-flat (7, 4) and its corresponding fret-string collection is situated below the seventh fret. This is done to approximate where Clark’s hand would be centered as she plays the chords. The chords connect via slurred arrows which illustrate the performative distance Clark traverses from each chord to the next. Below each slur in Arabic numbers is the distance value from each bass note calculated by the Cartesian formula.

Larger transitions also feature slightly thicker slurs. Finally, the double bar across the slur from chord 4 to 1 illustrates the restart of the harmonic cycle. 164

Fret 5 6 7 8 9 6: E-flat 5: B-flat String 4: G-flat 2 1 3: D-flat 4 3 2: A-flat 1: E-flat (5, 6) (7, 6) (0, 6) (0, 6) (5, 5) (6, 5) (8, 5) (9, 5) (5, 4) (7, 4) (7, 4) (7, 4) (8, 3) (9, 3)

4 || 1 2 17

Figure 6.4. A fretboard network of chord transitions, verse, “Paris is Burning,” 0’ 18’’ – 0’ 40’’.

Beginning on the left-center B-flat diminished chord, fret-string coordinate (7, 4), the

four-chord cycle of the verse is traced by the slurs, culminating in the harmonically

ambiguous tetrad built on A-natural (8, 3). D-flat (7, 4) acts as the verse’s performative (not

tonal!) center, as it initiates the formal cycle and establishes the main chord shape to be used

throughout the section. From this point, Clark enacts a series of relatively parsimonious

performance gestures around this D-flat, first by sliding down two frets to the A-flat minor

chord in first inversion (5, 4), and then making a much larger transition to the E-flat minor 165 seventh chord built on B-flat (8, 3). It is here that the notes on the D string (B-flat) and B string (G-natural) slide down one fret (a half step) to A-natural and G-flat respectively. This chord then shifts diagonally to return to the initiating chord.

Marked by the bolded slur, the most pronounced internal gesture occurs during the second chord transition, coinciding with a change in harmonic function and pitch structure.

E-flat, the middle note of the arpeggio in the second chord (5, 5), exchanges positions with its open-string counterpart in the third chord. In doing so, E-flat maintains its position as a sustained note in pitch space (thus its over-emphasis in the stepwise descent outlined above), while becoming the “highest” note in the vertical vector of the fretboard. But in another way, Clark’s relegation of the E-flat to an open string also makes the note inconsequential for performing the following chords, as open strings are effectively an ever-accessible fret located directly above or below any given fretted note, as described earlier. If the open string is ignored, the bracket-like chord-shape (in Koozin’s terms, the fret-interval vectors <212> and <313>) unifies the Verse, save for the second chord (tonic in first inversion). Ignoring the associated pitch (E-flat) in the linear descent through pitch-class space also shifts durational priority to the pitch D-flat, which is both the performative center and the third of the B-flat tonal center. The large shift from (5, 4) to (9, 3) gives weight to all of these considerations in pitch and instrumental space. This gesture is critical, as it signals a harmonic transition from a triadic to a tetradic chord structure, the tonic to dominant relationship between the A-flat minor chord and the E-flat dominant seventh chord and is perhaps a marker of the approaching harmonic ambiguity.

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Function and Performative-Thematic Unity

As likely evident, I find discussions of the melodic-harmonic divorce most compelling when approached from a performance-practice perspective. My question when listening is inevitably “Why does the melodic-harmonic divorce occur?” Even with support from Clark’s interviews, the issue of composer intent is almost always contentious. However, it is clear that Clark’s vocal and guitar parts do subscribe to an inherent parsimony under the song’s tonal framework. Where I argue these parts diverge harmonically is in Clark’s prioritization of affordances in the respective domain of vocal and guitar performance.

Like McCartney’s performative roles in “Hey Jude” from chapter three, I also advocate that Clark likely has a unified understanding of the song’s global tonal center (A- flat minor), but makes a rhetorical-compositional choice to separate the two domains in the verses, perhaps in light of the distinct parties represented in the lyrics of each formal zone: the verse describes a single individual (“I” as the solider), the prechorus mentions an opposing party (“They” as the enemy), and the chorus focuses on a group of individuals

(“We” whose affiliation is unclear). Evidence for this claim again comes from Clark’s guitar performance, where the separation of performative modalities in the verse eventually align in the chorus. Critically, the chorus acts as a point of thematic unity, where the theme from the introduction remerges in a new tonal context with newfound melodic and harmonic support from the guitar line. The distinct fretboard spaces between the verse and prechorus also align in the chorus. The subsequent close reading of the prechorus and chorus illustrates this unification process by providing a harmonic and performative overview of each zone and its respective internal and across-form transitions.

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Prechorus

Clark’s guitar part in the verse encompasses a horizontal range of five frets, from (5,

4) to (9, 3). The following prechorus meanwhile focuses on the lower register of the guitar neck near the headstock. Figure 6.5 offers a transcription of the melody, guitar and bass parts together and Figure 6.6 provides a transcription of the prechorus’s guitar part in tablature notation. The prechorus retains the same harmonic rhythm of the verse, with one chord per bar, comprising an overall harmonic shuttle between A-flat minor and G-flat major sonorities. The formal section begins clearly in A-flat, but as before, there is a distinct downward slide throughout the four-measure cycle. As this shift occurs, ambiguous and non-tertian harmonies arise. In the second chord the tonal center is not clear, even when supported by the melody. The same is mostly true for the third chord, though a G-minor chord briefly manifests via the D-natural in the melody and the lone B-flat featured in the guitar arpeggiation on beat 2.

Figure 6.5. Transcription of melody, guitar and bass parts, prechorus, “Paris is Burning,” 0’ 41’ – 1’ 07’’.

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Figure 6.6. Transcription of guitar part in tablature notation, prechorus to chorus, “Paris is Burning,” 0’ 41’’ – 1’ 07’’.

To move forward with the guitar performance analysis, matters of fretboard performance need clarifying. Figure 6.7 demonstrates that the transition from verse to prechorus occurs from (8, 3) to (2, 2). However, the actual sounded bass note of the A-flat minor chord is (0, 2), the open A-flat string. As argued earlier in the document, because open strings are effectively an infinitely accessible fret, A-flat can be articulated from any point on the fretboard, given that the second string is not already being fretted. But Clark still needs to slide her hand down the neck toward the headstock to play the fretted notes at

(2, 4) and (1, 5). To approximate this performative transition, I impose the fret of the next highest fretted string upon the next lowest open string. Thus (2, 2) acts as the performative center of this chord, or the place where (0, 2) and (2, 4) would converge on a coordinate

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plane. Because the fret-string position at (2, 2) is imagined or implied, the fret coordinate in

the box below the fretboard is intentionally greyed while the string coordinate remains in

black to show that the second string is still being plucked.

Fret 12 34 5678 9 6: E-flat 5: B-flat String 4: G-flat 2 1 3: D-flat 4 3 2: A-flat 1: E-flat Pre-chorus zone Verse zone (5, 6) (7, 6) (0, 6) (0, 6) (0, 5) (1, 5) (5, 5) (6, 5) (8, 5) (9, 5) (0, 4) (2, 4) (5, 4) (7, 4) (7, 4) (7, 4) (0, 3) (1, 3) (8, 3) (9, 3) (2, 2) (4, 1) ||

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Figure 6.7. Fretboard network of harmonic transitions, prechorus to chorus, “Paris is Burning,” 0’ 41’’ – 1’ 07’’.

In comparison to the verse, fretboard space becomes more parsimonious in the

prechorus. Reflecting this, the prechorus zone of Figure 6.7 does not feature slurs from each

chord, but rather dotted lines that point to bass notes. I define this as a feature of a positional

space. Unlike the verse, which featured a single chord shape that was transferred around the

central B-flat diminished chord at (7, 4), the entirety of the prechorus is played without any

170 horizontal movement.69 That is, Clark does not shift her hand from (2, 2) to produce any of the prechorus’s other chords. Instead, Clark plays each bass note via an open string (A-flat,

(0, 2) and D-flat (0, 3)), by barre with the index finger (D-natural, (1, 3)) or by extending the smallest finger (G-natural, (4, 1)) from the (2, 2) center.70 Clark’s use of this technique— separating the bass from the chordal accompaniment—reflects the guitar’s continued alignment with the electric bass part. The relatively constrained and consistent chord shape in the middle register meanwhile facilitates the passage’s playability.71

Similar functional markers also occur in the fretboard space between the prechorus and chorus, which is also transcribed in the above Figure 6.6. In contrast to the verse and the transition to the prechorus, Clark conveys hypermetric and formal boundaries with a different type of performance gesture—a release of physical energy through the use of an open-string G-flat major chord. In the first harmonic cycle, the release is fleeting, as Clark must reposition her fingers to play the A-flat minor chord to follow, a mere two frets away.

But in its repetition in the second rotation of the harmonic progression, a hypermetric extension grants her more time to “breathe” and prepare for the large gesture that initiates the Chorus. Here, the open-string chord acts as an opening up of the harmonic and performative space—G-flat major is presented in root position for the first time and the

69 Static chord shapes such as these, situated near the nut, are sometimes referred to as “cowboy chords” due to their playability. 70 As a whole, the harmonic structure of the prechorus zone is a byproduct of a highly idiomatic and performatively parsimonious space, made even more so through the use of open strings. 71 Such separation of textural layers is common in progressive rock styles. The introduction of “Closer to the Heart” by Rush (0’ 13’’), guitarist Alex Lifeson maintains a static chord shape in the upper register of the guitar while changing bass notes by (mostly) stepwise motion. Similar uses of cover tones in rock guitar performance occur frequently and is a facet of practice that warrants further investigation. 171 shift to (7, 6) is made easier by only requiring the use of the right hand to pluck the strings for the duration of the prechorus’s final measures.

Chorus

The primary formal cycle of “Paris is Burning” concludes with the initiation of the chorus. Unlike the other formal zones, the chorus is the most harmonically constrained and paradigmatic, consisting only of tonic and dominant harmonies in the key of A-flat minor. It is also proportionally the longest formal zone, featuring two complete stanzas as its four- measure cycle repeats four times instead of two as with the verse and prechorus. Figure 6.8 provides a transcription of the melody and guitar part in standard notation.

Figure 6.8. Transcription of vocal and guitar part, chorus, “Paris is Burning,” 1’ 09’’ – 1’ 20’’.

Starting on an E-flat, both the melody and accompaniment move together in harmonic and rhythmic unison on odd hypermetric beats. The even hyperbeats, in contrast, act as responses to the calls of the odd-measured end-accented phrases. And though the

172 even measures do provide the desired tonic harmony in the melody, the E-flat bass destabilizes their arrival, thus creating a second-inversion sonority that resolves downward to a root-position E-flat chord on beats two and four. It is not until the third bar of the chorus that a true perfect authentic cadence with a root position A-flat minor harmony occurs. As the chorus progresses from this first cadence, the tonal center of A-flat is confirmed three more times via root motion by ascending fourth.

Guitar-space transitions in the chorus articulate both fretboard zones outlined in the verse and prechorus. Shown in the tablature notation in Figure 6.9, the section begins like the verse, further up on the neck, centered around the seventh fret. As the first “response” measure occurs, Clark then shifts back down to the second fret to play an open-string voicing of the E-flat dominant. The constant shifting makes the Chorus the most performatively difficult and least parsimonious of all the formal zones. This also makes it the most auditorily complex through the frequent transitions in pitch space, in both the melody and accompaniment.

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Figure 6.9. Transcription of guitar part, chorus, “Paris is Burning,” 1’ 09’ – 1’ 32’’.

174 Performative and Narrative Unity

Unlike the previous formal zones, the melodic-harmonic divorce is virtually non- existent in the chorus by merit of doubling the melody with the guitar part in the “call” measures. In doing so, Clark effectively fuses her instrumental and vocal performative tasks.

The musical-embodied narrative created by this unity is quite compelling—by the time the chorus is reached, closure is obtained in the song’s performative, thematic, harmonic, and formal domains. Clark’s melody, which diverged from most of the harmonic content in previous sections, is now explicitly supported by the guitar part in rhythmic unison. The chorus’s melody evokes the top line of the opening chorale, providing thematic unity with a critical difference: the D-naturals heard in the introduction have become diatonic D-flats.

This in turn contributes to a sense of harmonic closure through a melodic descent, which also grants the formal closure that a listener might expect from a chorus.

Performatively, Clark also presumably experiences a similar sense of unity at the chorus. Preceding the chorus, each formal module is relatively parsimonious in its own right.

The verse centers around B-flat in a separate and mostly horizontal performative space and the prechorus subscribes to the same parsimony in a vertical space. In the chorus, however,

Clark links these spaces by alternating between the lower and upper register of the along- string vector of the fretboard.

This form-based separation of space is where the narrative perspective offered by the lyrics potentially intersects with performance practice. As shown in Figure 6.10, the verse’s use of first person coincides with a harmonic separation between the voice and guitar. The protagonist is presumably in isolation from others, stealing away to write a letter to home in the along-string domain of the keyboard. In the following prechorus, the narrative 175 perspective then shifts to that of a third party, “they” as the enemy. In tandem, Clark shifts the guitar space to the lower register and the harmonic ambiguities lessen as the melody becomes tight knit with the harmony in a mostly vertical fretboard space. In doing so, Clark creates a formal distinction between the narrator (verse, along-string, upper register) and the enemy or other party (prechorus, cross-string, lower register). The arrival of the chorus meanwhile creates a direct link between two parties through Clark’s alternation between fretboard spaces (upper and lower), performance styles (along-string and cross-string) and by reconciling the melodic-harmonic divorce with simple diatonic harmonies (tonic and dominant in A-flat minor) in reference to the previously chromatic but now diatonic opening theme.

Style and Practice

I will not go as far as to say that Clark’s articulation of these features in “Paris is

Burning” are intentional. And in my defense, interviews with the musician suggest that neither would Clark:

But I’m realizing now that – to be honest – music is a mystery to me. My own instincts, though I very much trust them now, are mysterious in their origin and ultimately I’m only ever trying to get at the sound that is there. And I’m going to try to bridge that gap between the theoretical and the actual.72

Rather, I offer this analysis to illustrate the rich interpretive potential of performance- practice perspectives as a way to synthesize listener and producer perspectives in popular

72 “St. Vincent: ‘I have this sound in my head. How do I get it here in my fingers?’” Salon Magazine, Moody 2014 (https://www.salon.com/2014/02/16/ st_vincent_i_have_this_sound_in_my_head_how_do_i_get_it_here_in_my_fingers/). 176

Narrative Melodic-harmonic Form Lyrics Fretboard space perspective relationships Verse I write to give word the war is over First-person Loose-knit to tight-knit Horizontal movement/ Send my cinders home to mother Divergence upper register They gave me a medal for my valor Loose-knit to tight-knit Leaden trumpets spit the soot of power Divergence Prechorus They say, "I'm on your side Third-person Tight-knit with melodic Vertical movement/ "When nobody is, 'cause nobody is embellishments lower register "Come sit right here and sleep "While I slip poison in your ear" Chorus We are waiting on a telegram First-person plural Harmonic and rhythmic unity Horizontal/upper To give us news of the fall Background vocals Vertical/lower I am sorry to report First-person singular Harmonic and rhythmic unity Horizontal/upper Dear Paris is burning after all Background vocals Vertical/lower Chorus We have taken to the streets First-person plural Harmonic and rhythmic unity Horizontal/upper In open rejoice revolting Background vocals Vertical/lower We are dancing a black waltz Harmonic and rhythmic unity Horizontal/upper Fair Paris is burning after all Background vocals Vertical/lower

Figure 6.10. Gradual harmonic, melodic, and narrative-perspective unification across the forms of “Paris is Burning.”

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music analysis. De Souza’s work (2017; 2018) does this well, but I continue to maintain that addressing the most prevalent issues in popular-music analysis, like the melodic-harmonic divorce, are only made clearer when considering how and even speculating why producers like

Clark create the sounds that they do.

In comparison to other chapters, my approach to the ambiguities in “Paris is

Burning” is strictly hermeneutic. However, this close reading still reinforces findings from other chapters. For example, Clark’s transition to each formal zone coincides with the song’s largest transitions in instrument space, upholding the Form and Transition principles supported by statistical tests in chapters 3, 4 and 5. Clark also generally maintains the

Harmony and Parsimony principles within each formal boundary; the non-tertian harmony

(A-Db-Eb-G) in the verse, for example, is simply a byproduct Clark maintaining fretboard affordances by shifting the outer notes of the previous chord shape down by one fret.

In terms of style categorization, it is not clear whether listeners would classify this song as either “pop” or “rock.” I would argue either label is largely inappropriate, as the tonal framework clearly evokes common-practice harmony to some degree, while performance practice also makes a case for both pop and rock styles. Voice leading and the prechorus and chorus’s emphasis on tonic and dominant harmonies in A-flat minor specifically reinforce the song’s common-practice influence, which I argue at the start of this chapter may be due to Clark’s formal training.

The synthesis of pop and rock styles meanwhile occurs mostly by formal zone. In the verse, Clark shifts her chord shapes mostly by descending second, which evidence from the Modal-Pentatonic and Function corpus suggests indicates a rock style. These harmonic 178 transitions also occur primarily in the horizontal or along-string domain of the fretboard, the space in which participants from the motion-capture study were most mobile when playing in a rock style. The open-string voicings in the prechorus meanwhile suggest this zone is more indicative of a pop style. Clark also maintains the highest degree of horizontal parsimony in this domain, which again aligns with the pop performances from the motion- capture study. The lack of overdrive also provides a timbral orientation toward pop. With the synthesis of these two forms in the chorus, it appears as if the label “pop-rock” best characterizes Clark’s performance of “Paris is Burning,” at least when considering performance practice.

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7. Chapter 7: Conclusion

In some circles of popular-music performers, there is a curious resistance to “music theory,” especially for guitarists. I half-heartedly place the word “music theory” into scare quotes because what many of these performers seem to mean by the term is a grounding the fundamentals of pitch—namely scales and basic (albeit common-practice modeled) harmony. And while I am occasionally frustrated at the public misconception of what music theory is—or what it could be in popular-music theory—the evidence of uneasiness toward music theory is profuse. A quick search on the community forums on ultimate-guitar.com reveals multiple posts on the subject, such as “Is Reading Music A Necessary Skill for

Guitarists?”, “Can Music Theory Improve Your Songwriting”, or “Should I Learn Music

Theory?”

It would be easy to write off this trend as poor messaging or a misconceptualization of the goals of music theory on behalf of the writers of these posts. Such a stance, however, poses an inherent risk of elitism and ultimately reveals that music theorists, not the performers, are perhaps the ones who are out of touch. Even successful mainstream artists grapple with the perceived need for an a priori knowledge of theory for performance.

Echoes arise in the firsthand accounts presented in this document: Annie Clark notes she does not want to have so much skill that she “can presuppose the outcome” and, about her guitar playing, claims that “…music is a mystery to me… I’m trying to bridge that gap between the theoretical and the actual [with my guitar]” (Moody 2014). Brittany Howard argues the very same, stating that “technical stuff don’t matter to me… I like not knowing it.

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It’s a mysterious element and then everything I do is like, magical when I find out about it”

(Rena 2017). Nancy Wilson responds similarly when asked “You said you’ve never had guitar lessons. Do you regret not taking more formal instruction?”:

No. For me, and for this kind of music, playing by ear is the most important thing. So many people I know became confined by their learning to the point where they couldn’t really feel the music, or venture out into their own imaginary wanderings (Wheeler 2020).

Ulitimate-guitar.com also features a collection of articles on the subject, such as “Tom Morello

Answers: Does Music Theory Block a Guitarist’s Creativity?”

The amalgamation of these quotes suggest that some artists believe formal training or theoretical knowledge are incompatible with creativity. And though this notion may seem quizzical to listeners, it is precisely why Steve Vai feels it is necessary to present Vaideology as a music theory textbook for guitarists: to reintegrate theory and practice to make music theory accessible to alienated guitarists.

Music theory can also benefit from such an approach. There are numerous unique organizational features of popular music that resist analysis under traditional functional models. Considering how and why these features arise in practice provides additional clarity, especially when perceptually accessible statistical-secondary parameters (e.g., timbre, texture) contextualize syntactic-primary parameters (e.g., harmony). That is, if an analyst positions themselves as a producer who has a tacit (i.e., statistical, but not necessarily theoretical) knowledge of popular music, traditional assumptions about hierarchy may fall away in favor of more immediate concerns, such as the position of a performer’s hand on their instrument or the timbral profile of an artist they wish to emulate. In this document I focus on guitar

181 performance, but I also find that similar performative priorities also occur in keyboard-based popular-music songs.

David Paich, keyboardist and songwriter for Toto, highlights how modality, instruments, embodied performance and auditory complexity in terms of style all act as unique pressures on musical development. In the following quote, Paich describes how his instrument effectively acts an agent who shapes musical structure when composing “Hold the Line”:

It started out with the piano riff that is in the intro. I started playing this riff and I just couldn't stop playing it. I played it for days, and I started singing, "Hold the line, love isn't always on time." It was a phrase that just came into my head. . . it was a blessing. [The words] came to me in the night, and then I went to the verse. I wrote it in 2 hours. Sometimes songs come quickly like that, and sometimes I spend 2 years trying to finish a song. …in New York they called it a doo-wop song, which are songs guys used to sing on the street corner. But I never saw it like that, because I was more influenced by Sly & The Family Stone’s “Hot Fun in the Summertime.” I mean, that’s where that triplet feel really came from for me.73

The rhythmically active riff, transcribed in the electric piano part of Figure 7.1, features a syncopated harmonic rhythm on chord roots F#, A, B, and E. Its four-chord shuttle serves as the primary harmonic material for the chorus and the function of its constituent chords falls into a tonic (F# and A), predominant (B), dominant (E-Esus4-E) phrase model. But did these harmonic concerns matter to Paich as he played the riff again and again? Or was its main attraction that it captured the rhythmic energy of Sly & The Family Stone’s “Hot Fun

73 http://www.toto99.com/blog2010/index.php?/archives/739-HOLD-THE-LINE.html 182 in the Summertime,” the song’s stylistic inspiration? At a more visceral level, it seems the repetition was simply satisfying to play, as implied by the quote above.

Figure 7.1. Primary keyboard riff of “Hold the Line” by Toto, composed by Paich.

Paich’s account prioritizes the following processes: his interaction with his instrument, concerns of form, and pressures of style, influence, and preference. These components are inexplicably intertwined. By interacting with the keyboard, with the influence of “Hot Fun in the Summertime” in mind, Paich generates a rhythmically active musical texture that is satisfying to play. As he repeats the riff, he feels a need for a change in texture, which in turn encourages a change in form. But in the process, Paich’s compositional choices also constrain his movements in keyboard space. By emulating the fast triplets of “Hot Fun in the Summertime,” the riff itself is necessarily parsimonious because of Fitts’s Law. As demonstrated in Figure 7.2, at most Paich moves two notes by step in keyboard space when transitioning between chords. When a large shift in instrument space does occur, it happens at the hypermetric boundary (i.e., the repetition of the riff) and the transition to the verse.

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A harmony-oriented approach to musical structure gives the agency of understanding to the listener. Following Hatten’s theory of virtual agency, often pitches and harmonies themselves are treated as “virtual agents” who serve to “simulate the actions, emotions, and reactions of a human agent” (2018, 1). But again, Paich downplays the harmonic influence of the “doo-wop” style, which is traditionally associated with a specific harmonic progression.

Instead Paich speaks to the physical process of shaping the riff.

So I ask: how can harmony, as a virtual agent, a symbol meant to evoke a heard sonority, and an icon without a physical body, capture the act of placing one’s hands on a keyboard and repeating a riff so much that it evokes an experienced sense of satisfaction?

Zbikowski’s treatment of Barsalou’s theory of perceptual symbols addresses this partially, arguing that a harmonic symbol can represent multiple cognitive and perceptual modalities, including audiation and physical responses to music. Nevertheless, there is still a disconnect between the symbol “F# minor,” as music theorists typically treat it, and Paich’s keyboard performance. That is, even though parsimony in pitch-class space is a fair approximation of the instrumental parsimony Paich maintains as he plays the riff, there are other stylistic pressures at play (namely rhythmic syncopation) in the functional organization of “Hold the

Line.” The chord symbol “F# minor” only points to pitch as one stylistic component: one that Paich seemingly deprioritizes. Moreover, by pushing back against perceived allusions to

“doo-wop,” Paich suggests that a series of chords does not reflect his priorities as reflected in his work.

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Figure 7.2. Primary riff for “Hold the Line” by Toto, composed by David Paich. The graph below demonstrates the number of half-step transitions from chord to chord.

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Summary

My primary goal with this study is to provide analysts with the methodological framework and resources to consider multiple organizational parameters of popular music.

My focus is primarily on guitar performance practice, as I find professional, semi- professional and amateur guitarists often have a curious relationship with music theory.

From preliminary analyses of guitar riffs, I devise a set of five performance practice principles which offer a performer-based perspective on the functional organization of popular music from the perspective of the guitar fretboard. I then test the validity of these principles through various analyses: computationally in a corpus of modal-pentatonic rock songs and in a historically expanded collection of pop and rock songs, behaviorally in the real-time performances of practicing musicians, and hermeneutically in a close reading of

“Paris is Burning” by Annie Clark.

Each of these analyses suggest that performers generally prefer to maintain parsimony in fretboard space, regardless of harmonic content, and coordinate larger gestures with shifts in hierarchical-temporal structure such as changes in hypermeter and form. I also outline harmonic and performative differences between pop and rock music as socially determined styles, which broadly suggests that performers associate rock performance with along-string movement, while pop performance occurs primarily in the cross-string domain of the fretboard. This contributes to key harmonic differences between the styles.

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Future Work

I also recognize that this study ultimately raises more questions than it answers. The bulk of my approach is empirical and involves the parsing and analysis of a full-textured or fully realized corpus of popular-music songs. One could argue that such a corpus is potentially unwieldly and that by using crowd-sourced transcriptions I run the risk of analyzing poorly compiled or inaccurate source materials. However, I do take steps to mitigate these issues (e.g., parsing for specific parameters and checking scores for quality alongside other analysts).

That being said, like de Clercq and Temperley do of the Rolling Stone 200, I view the

Function corpus as a developing database. My goal moving forward is to continue to clean and add additional high-quality transcriptions to the database so that it becomes a comprehensive and socially inclusive reflection of popular music from the 1950s to the present. With this, I hope to further clarify issues raised in this dissertation, especially in relation to style and performance practice. Here the full transcriptions will likely prove advantageous, as I can coordinate metadata (e.g., genre information) provided by ultimate- guitar.com with rhythmic, harmonic, melodic and textural information (e.g., nPVI, melodic/harmonic intervals, instrumentation) from the scores to conduct a machine-learning study that assesses which parameters contribute most strongly to a “pop” or “rock” designation. This, I believe, will help to further disambiguate this otherwise murky distinction between styles under the umbrella of popular music.

As evidenced by the analysis of “Hold the Line” above, I also speculate that the performance practice principles I outline for guitar may also apply to keyboard riffs. Both

187 empirical (i.e., corpus-based) and behavioral (i.e., motion-capture) data will be necessary in this pursuit. As a theoretical framework, Duguay’s (2019) model of balance offers the most promise, as she provides an intuitive and computationally straightforward method for relating hand and body position to large-scale hierarchical structures such as hypermeter and form.

The performative aspects of the melodic-harmonic divorce also warrant further discussion. My analysis of “Paris is Burning” suggests that idiomaticism plays a large part in

Clark’s separation of vocal and guitar lines. However, style and rhetoric are also obvious due influences. This speaks to the potentially overwhelming number of communicative pressures

(Temperley 2004) producers experience as they generate music in real time. Again, a large- scale and perhaps empirical assessment is necessary. It would also be interesting to conduct a behavioral analysis to determine which musical parameters (e.g., pitch, rhythm, texture) contribute most strongly to a listener’s perception of dissonance when encountering instances of the melodic-harmonic divorce.

Finally, expertise and stylistic preferences are also important factors on the development and execution of musical textures. In the motion-capture study, I do not account for a participant’s experience in its statistical models, however my anecdotal experiences with the participants suggests that most were most comfortable playing in a rock style. Moreover, less experienced players tended to be more conservative with their movements overall. Given Clark’s impressive execution of parallel thirds in the chorus of

“Paris is Burning,” it also seems obvious that there is a relationship between training or experience and accuracy as a factor of Fitts’s Law.

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Appendix A: The Biamonte Modal-Pentatonic Corpus

Form: Harmonic patterns: I = Introduction V = Verse Pentatonic 1: (1 flat-3 4 5 flat-7) C = Chorus Pentatonic 3: (1 2 4 5 flat-7) S = Solo Sp = Strophe Pentatonic 4: (1 flat-3 5 flat-6 flat-7) R = Refrain Pentatonic 1/4 subsets: (1 flat-3 5 flat-7) Ie = Interlude B = Bridge Pentatonic 4 subsets: (1 flat-3 4 flat-6), (1 4 flat-6 flat-7) P = Prechorus no [1-7] = scale degree not included in representative passage Z = Postchorus St = Statement Re = Restatement De = Departure Co = Conclusion O = Outro

Artist Song Formal Organization Harmonic Pattern ACDC Back In Black I V1 C1 V2 C2 S1 C3 B C4 O double plagal, pentatonic 1 Aerosmith Dream On I V1 C1 V2 C2 S1 C3 B C4 O aeolian Alice Cooper Elected I V1 V2 C1 V3 C2 B V4 C3 O aeolian-dorian no 6 Alice Cooper I'm Eighteen I V1 C1 V2 C2 S1 V3 C3 O aeolian

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Appendix A continued Artist Song Formal Organization Harmonic Pattern Black Sabbath Paranoid I V1 V2 R V3 S1 V4 V5 O aeolian Bon Jovi Livin on a Prayer I V1 P1 C1 V1 P2 C2 S1 P3 C3 O aeolian, pentatonic 1-4 Bon Jovi Wanted I V1 C1 Ie1 V2 C2 Ie2 S1 C3 V3 C4 Ie/O pentatonic 1-4 Cream Sunshine of Your Love I V1 C1 V2 C2 S1 V3 C3 pentatonic 1-4 David Bowie Suffragette City I V1 V2 C1 V3 C2 S1 C3 C4 O aeolian no 3 Deep Purple Child in Time I V1 C1 S1 S2 S3 S4 V1 C2 O aeolian Deep Purple Hush I Ie1 V1 Ie2 C1 Z1 V2 Ie3 C2 Z2 S1 O pentatonic 4 ELO Don't Bring Me Down I V1 V2 C1 V3 V4 C2 Ie1 V5 O6 pentatonic 1-4 Eric Clapton Let it Grow V1 C1 V2 C2 S1 S2 V3 C3 aeolian no 2 Golden Earring Radar Love I Ie1 V1 P1 C1 Ie1 V2 P2 C29 B17 S1 B2 Ie3 V3 C3 O5 aeolian no 2 G. F. Railroad We're An American Band I V1 P1 C1 V2 P2 C2 S1 C3 O aeolian Guns n’ Roses Sweet Child O Mine I V1 C1 V2 C2 S1 C3 S2 S3 B6 O2 double-plagal Heart Barracuda I V1 C1 Z1 V2 C2 Z2 B1 S1 C3 S2 O1 aeolian no 5 Heart Crazy on You I V1 P1 C1 V2 P2 C2 B1 C3 V3 C4 S1 B2 C5 aeolian Iron Maiden Number of the Beast I V1 V2 Ie1 V3 C1 V4 C2 S1 S2 Ie3 S3 Ie4 V5 C3 V6 O aeolian no 2 Jimi Hendrix Voodoo Child I I2 Sp1 R1 S1 Sp2 R2 S2 O1 aeolian JJ Cale Cocaine I Sp1 R1 Ie1 Sp2 R2 Ie2 S1 Sp3 R3 O mixolydian J. C. Mellencamp ROCK in the USA I V1 C1 V2 S1 V3 C2 O double-plagal

198

Appendix A continued Artist Song Formal Organization Harmonic Pattern

Kansas Carry On My Wayward Son I I2 V1 V2 C1 Z1 V3 V4 C2 Ie1 S1 Ie2 S2 Ie3 aeolian P1 C3 Ie4 S3 Ie5 O

Led Zeppelin Communication Breakdown I V1 C1 V2 C2 S1 C3 O1 double-plagal Led Zeppelin Immigrant Song I V1 C1 V2 Ie1 V3 C2 Z1 O1 locrian, no b2 or b6 Led Zeppelin Stairway to Heaven I V1 R1 V2 Ie1 R2 V3 R3 V4 R4 V5 R5 V6 R6 V7 O6 aeolian Mountain Mississippi Queen I Sp1 R1 Sp2 R2 Sp1 R3 O pentatonic 1 Nirvana Smells Like Teen Spirit I V1 P1 C1 Z1 V2 P2 C2 Z2 S1 V3 P3 C3 O pentatonic 1-4 Patti Smith Because the Night I V1 P1 C1 V2 P2 C2 S1 B1 P3 C3 O aeolian Pink Floyd Another Brick in the Wall, pt 2 V1 C1 V2 C2 S1 O dorian Queen Crazy Little Thing Called Love I Sp1 R1 Sp2 R2 B1 Sp3 R3 Sp1 Sp4 R4 Sp5 R5 O pentatonic 1-4 REM The One I Love I V1 C1 V2 C2 S1 V3 C3 O aeolian Romantics What I Like About You I V1 C1 V2 C2 B1 S1 V3 C3 O double-plagal Rush Jacobs Ladder I V1 Ie1 S1 S2 S3 Ie2 Ie3 Ie4 Ie5 O1 phrygian, no 5 Scorpions No One Like You I V1 C1 V2 C2 O aeolian Scorpions Rock You Like a Hurricane I V1 C1 V2 C2 S1 V3 C3 O4 pentatonic 4 Sex Pistols I'm Not Your Stepping Stone I R1 S1 R2 S2 R3 Ie1 R4 S3 R5 O pentatonic 4 subsets Steppenwolf Born to be Wild I V1 P1 V2 P2 C1 S1 V3 P3 C23 O1 mixolydian Styx Renegade V1 V2 C1 V3 C2 S1 B1 V4 C3 O dorian Talking Heads And She Was I V1 P1 C1 Z1 V2 P2 C2 B V3 P3 C3 O6 double-plagal The Beatles Everybody's Got Something To I Sp1 R1 Sp2 R2 Sp3 R3 O pentatonic 1 Hide

199

Appendix A continued Artist Song Formal Organization Harmonic Pattern The Beatles Here Comes the Sun I C1 V1 C2 V2 C3 B V3 C4 C54 O2 pentatonic 1 The Beatles Hey Jude V1 V2 C1 V3 C2 V4 O double-plagal The Beatles Taxman I Sp1 R1 Sp2 R2 Sp3 R3 S1 R4 Sp3 R5 Sp5 R6 S2 double-plagal The Beatles With a Little Help From My I V1 C1 V2 C2 B1 V3 C3 B2 C3 double-plagal Friends The Doors Break on Through I V1 C1 V2 C2 S1 B V3 C3 S2 V4 C4 O Aeolian The Doors Love Me Two Times I V1 C1 V2 C2 S1 Ie1 V3 C3 V4 C4 O4 hexatonic aeolian no 2 The Doors Riders on the Storm I V1 V2 S1 V3 S2 Ie1 V4 S3 O9 dorian The Kinks Lola I St1 Re1 De1 Co1 B St2 De2 Co2 O double-plagal The Knack My Sharona I V1 P1 C1 V2 P2 C2 S1 Ie1 V3 P3 C3 S2 O pentatonic 4 The Moody Blues Nights in White Satin I V1 V2 C1 V3 V4 C2 S1 V5 V6 C3 O4 phrygian, no 5 The Pretenders Middle of the Road I V1 C1 V2 C2 S1 B5 V3 C3 S2 O1 pentatonic 1 The Rolling Stones Brown Sugar I V1 C1 V2 C2 S1 C3 V3 C4 O hexatonic aeolian no 2 The Rolling Stones Gimme Shelter I V1 C1 V2 C2 S1 B V3 C3 O3 aeolian The Rolling Stones Not Fade Away I Sp1 R1 Sp2 R2 So1 Sp3 R3 double-plagal S. Davis Group Gimme Some Lovin I V1 C1 Ie1 V2 C2 Ie2 V3 C3 O pentatonic 1-4 The Who Love Ain't For Keepin I V1 C1 V2 C2 S1 C3 O pentatonic 1-4

200

Appendix A continued Artist Song Formal Organization Harmonic Pattern The Who See Me, Feel Me C1 V1 V2 V3 hexatonic aeolian no 2 ZZ Top Sharp Dressed Man I Sp1 R1 Sp2 R2 S1 Ie1 Sp3 R3 S2 O double-plagal

201

Appendix B:

The Pop-rock Function Corpus

Annotator Test GP ID Song Artist Style Decade album year Diverse Moore 1 214915 No Particular Place To Go Chuck Berry rock 1960 1964 1 Moore 1 216018 Army Dreamers Kate Bush pop 1980 1980 1 Moore 1 216019 Wuthering Heights Kate Bush pop 1970 1978 1 Moore 1 216358 Baby Can I Hold You Tracy Chapman rock 1980 1988 1 Moore 1 219004 Going Under Evanescence rock 2000 2003 1 Moore 1 219452 Rhiannon Fleetwood Mac rock 1980 1975 1 Moore 1 219856 Stupid Girl Garbage rock 1990 1995 1 Moore 1 221002 Crazy On You Heart rock 1970 1975 1 Gardner 1 223462 Again Lenny Kravitz rock 2000 2000 1 Gardner 1 223468 Believe Lenny Kravitz rock 1990 1993 1 Gardner 1 224212 Let It Go Loudness rock 1980 1986 1 Gardner 1 224407 Like A Virgin Madonna pop 1980 1984 1 Gardner 1 224410 Papa Don’t Preach Madonna pop 1980 1986 1 Gardner 1 229470 Self Portrait Rainbow rock 1970 1975 1 Gardner 1 230541 Oye Como Va Santana rock 1970 1970 1 Gardner 1 231127 Goodnight Moon Shivaree rock 1990 1999 1 Gardner 1 231383 El Vals Del Obrero Ska-P rock 1990 1996 1 Gardner 1 232202 Wannabe Spice Girls pop 1990 1996 1

202

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Wood 1 234858 Dead Leaves And The Dirty Ground The White Stripes rock 2000 2001 1 Wood 1 235190 Rue De La Paix Zazie pop 2000 2001 1 Wood 1 240739 Alone Heart rock 1980 1987 1 Wood 1 347488 Blitzkrieg Bop Ramones rock 1970 1979 1 Wood 1 349599 The Crowing Coheed and Cambria rock 2000 2003 1 Wood 1 389614 Rock Lobster The B-52's pop 1970 1978 1 Wood 1 418565 Huwag Mo Nang Itanong Eraserheads rock 1990 1995 1 Nichols 1 420428 Neighborhood 3 Power Out Arcade Fire pop 2000 2004 1 Nichols 1 475182 Bitch Meredith Brooks rock 1990 1997 1 Nichols 1 475892 I Don’t Feel Like Dancin Scissor Sisters pop 2000 2006 1 Nichols 1 478659 Raspberry Beret Prince rock 1980 1985 1 Nichols 1 535845 Amateur Molotov rock 2010 2004 1 Nichols 1 542854 Live and Learn Crush 40 rock 2000 2001 1 Nichols 1 558077 Blackfield Blackfield rock 2000 2004 1 Nichols 1 563298 Frijolero Molotov rock 2000 2003 1 Nichols 1 568250 Umbrella Rihanna pop 2000 2008 1 Nichols 1 570270 Gomenasai t.A.T.u. pop 2000 2006 1 Shea 1 573577 Viva Las Vegas Dead Kennedys rock 1980 1980 1 Shea 1 583982 Kill The Poor Dead Kennedys rock 1980 1980 1 Shea 1 585673 A Moment Like This Kelly Clarkson pop 2000 2003 1 Shea 1 594870 Take It Off The Donnas rock 2000 2009 1 Shea 1 617061 A Favor House Atlantic Coheed and Cambria rock 2000 2003 1 Shea 1 646265 Por La Boca Vive El Pez Fito & Fitipaldis rock 2010 2017 1 Shea 1 674146 Indiana Hombres G pop 1980 1986 1

203

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Moore 1 683875 Knowing Me Knowing You ABBA pop 1970 1976 1 Wood 1 699445 One Armed Scissor At the Drive-In rock 2000 2000 1 Shea 1 748004 Gravemakers And Gunslingers Coheed and Cambria rock 2000 2007 1 Moore 1 786774 Andmoreagain Love rock 1960 1967 1 Moore 1 828925 Inevitable Shakira pop 1990 1998 1 Moore 1 830288 Again Archive rock 2000 2002 1 Moore 1 852239 Love Story Taylor Swift rock 2000 2008 1 Moore 1 889228 Ariel Rainbow rock 1990 1995 1 Moore 1 892161 Dreams We Came As Romans rock 2000 2009 1 Moore 1 909387 Hero Skillet rock 2000 2009 1 Moore 1 920106 A House Is Not A Motel Love rock 1960 1967 1 Gardner 1 953860 I Was A Teenage Anarchist Against Me! rock 2010 2015 1 Gardner 1 955669 Angels Walk Among Us Anathema rock 2010 2011 1 Gardner 1 991011 Take It Off Kesha pop 2010 2010 1 Gardner 1 1009443 Shampain Marina and The Diamonds pop 2010 2010 1 Gardner 1 1038413 Me Against The Music Britney Spears pop 2000 2003 1 Wood 1 1136515 Terrified Katharine McPhee pop 2010 2010 1 Wood 1 1145845 Joey Concrete Blonde rock 1990 1990 1 Wood 1 1146907 Gloria YUI pop 2010 2012 1 Wood 1 1162667 Always Summer Yellowcard rock 2010 2012 1 Wood 1 1164632 Real Talk Bloc Party rock 2010 2012 1 Wood 1 1211036 Now Paramore rock 2010 2013 1 Wood 1 1236142 Mistral Wind Heart rock 1970 1978 1 Nichols 1 1425491 Afuera Caifanes rock 1990 1994 1

204

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Nichols 1 1426464 Locked Out Of Heaven Bruno Mars pop 2010 2012 1 Nichols 1 1431730 Shouldnt Come Back Demi Lovato pop 2010 2013 1 Nichols 1 1433998 Hope We Came As Romans rock 2010 2013 1 Nichols 1 1443348 The Wire HAIM rock 2010 2013 1 Nichols 1 1447235 Going To Hell The Pretty Reckless rock 2010 2014 1 Nichols 1 1458360 The State Of Dreaming Marina and The Diamonds pop 2010 2012 1 Nichols 1 1464198 Top Of The World Carpenters pop 1970 1972 1 Nichols 1 1477155 Angel Sarah McLachlan pop 1990 1997 1 Nichols 1 1478934 Go Your Own Way Fleetwood Mac rock 1970 1977 1 Nichols 1 1480892 Angels The xx rock 2010 2012 1 Sam The Sham Shea 1 1694106 Lil Red Riding Hood & The Pharaohs rock 1960 1966 1 Shea 1 1721849 Youve Got The Love Florence + The Machine pop 2000 2009 1 Shea 1 1730722 Never As Good As The First Time Sade pop 1980 1985 1 Shea 1 1772361 Visite Nuestro Bar Hombres G pop 1980 1986 1 Moore 1 1805288 Exs And Ohs Elle King rock 2010 2015 1 Moore 1 1810442 Ppp Beach House rock 2010 2015 1 Wood 1 1886343 Aint That Peculiar Marvin Gaye pop 1960 1966 1 Wood 1 1979745 Zephyr And I Suzanne Vega pop 2000 2007 1 Nichols 1 2008553 Sparks Fly Taylor Swift pop 2010 2010 1 Nichols 1 2038460 Girls Just Want To Have Fun Cyndi Lauper pop 1980 1983 1 Nichols 1 2049010 Symphonie Silbermond pop 2000 2004 1 Nichols 1 2062063 Right There Nicole Scherzinger pop 2010 2011 1 Shea 1 2075567 Sweet Sweet Smile Carpenters pop 1970 1977 1

205

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 1 2374605 Me Enamore Shakira pop 2010 2017 1 Shea 1 2497368 Head Above Water Avril Lavigne pop 2010 2019 1 Shea 1 2525562 Snowbird Anne Murray pop 1960 1969 1 Shea 1 2582598 Kiss Me Deadly Lita Ford rock 1980 1988 1 Shea 1 2784439 To Sir With Love LuLu pop 1960 1967 1 Moore 1 213647 You Don’t Believe The Alan Parsons Project pop 1980 1984 0 Moore 1 214859 I Started A Joke Bee Gees pop 1960 1968 0 Moore 1 215435 Going Away To College Blink-182 rock 1990 1999 0 Moore 1 216433 The Red Chevelle rock 2000 2002 0 Moore 1 216873 Cant Stop Loving You Phil Collins pop 2000 2002 0 Moore 1 217288 She Rides Danzig rock 1980 1988 0 Moore 1 218781 My Beloved Monster Eels pop 1990 1996 0 Moore 1 219346 This Fire Franz Ferdinand rock 2000 2004 0 Moore 1 220174 La Pluie Jean-Jacques Goldman pop 2000 2001 0 Moore 1 220212 Tournent Les Violons Jean-Jacques Goldman pop 2000 2001 0 Moore 1 220486 When I Come Around Green Day rock 1990 1994 0 Gardner 1 221219 The Boys Of Summer Don Henley rock 1980 1984 0 Gardner 1 221798 Mao Boy Indochine pop 2000 2002 0 Gardner 1 221806 Salombo Indochine pop 1980 1985 0 Gardner 1 225963 For My Lady The Moody Blues pop 1970 1972 0 Gardner 1 226282 The Remedy I Wont Worry Jason Mraz pop 2000 2002 0 Gardner 1 228337 Its A Sin Pet Shop Boys pop 1980 1987 0 Gardner 1 228443 Lost For Words Pink Floyd rock 1990 1994 0 Gardner 1 228719 Good Rockin Tonight Elvis Presley rock 1950 1954 0

206

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Gardner 1 230042 Mon Beauf Renaud pop 1980 1981 0 Gardner 1 230450 Witch Hunt Rush rock 1980 1981 0 Gardner 1 232370 Pictures Of Matchstick Men Status Quo rock 1960 1968 0 Wood 1 234845 When The Children Cry White Lion rock 1980 1987 0 Wood 1 235123 Cinnamon Girl Neil Young rock 1960 1969 0 Wood 1 235216 Demon Speeding Rob Zombie rock 2000 2003 0 Wood 1 239610 Over Under Sideways Down The Yardbirds rock 1960 1966 0 Wood 1 261752 You’re Beautiful James Blunt pop 2000 2004 0 Wood 1 339123 Lying Is The Most Fun A Girl Can Have Panic! At the Disco rock 2000 2005 0 Without Taking Her Clothes Off Wood 1 397282 Mellow Yellow Donovan pop 1960 1966 0 Wood 1 419497 Marchewkowe Pole Lady Pank pop 1980 1988 0 Nichols 1 430808 Wild West End Dire Straits rock 1970 1978 0 Nichols 1 436621 Lift Me Up Moby pop 2000 2005 0 Nichols 1 456983 Metal Health Bang Your Head Quiet Riot rock 1980 1983 0 Nichols 1 471451 Its Only Love Bryan Adams rock 1980 1984 0 Nichols 1 471930 Nights On Broadway Bee Gees pop 1970 1975 0 Nichols 1 472304 All The Rage Funeral for a Friend rock 2000 2005 0 Nichols 1 473714 Substitute The Who rock 1960 1968 0 Nichols 1 486182 Matchbox The Beatles pop 1960 1964 0 Nichols 1 538969 Ma‚âà√áa Wojna Lady Pank pop 1980 1988 0 Nichols 1 550115 All That’s Left Thrice rock 2000 2003 0 Nichols 1 551460 The Way Fastball rock 1990 1998 0 Shea 1 585675 I Knew I Loved You Savage Garden pop 1990 1999 0

207

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 1 604911 How Long Eagles rock 2000 2007 0 Shea 1 666553 River Constantine Jars of Clay pop 1990 1999 0 Shea 1 682720 Spending My Time Roxette pop 1990 1995 0 Moore 1 687780 Paint Roxette pop 1980 1988 0 Gardner 1 689439 The Look Roxette pop 1980 1988 0 Wood 1 694884 Midnight Blues Gary Moore rock 1990 1990 0 Wood 1 697616 Massacre Thin Lizzy rock 1970 1976 0 Wood 1 723058 The One Backstreet Boys pop 1990 1999 0 Wood 1 733038 Yellow Coldplay rock 2000 2000 0 Shea 1 739332 Missing You John Waite rock 1980 1984 0 Shea 1 743914 Walk Like A Man The Four Seasons pop 1960 1963 0 Shea 1 744027 How Can You Mend A Broken Heart Bee Gees pop 1970 1971 0 Shea 1 751243 No Time The Guess Who rock 1960 1969 0 Shea 1 777175 Now That Were Done Metro Station pop 2000 2008 0 Moore 1 808740 Central John Frusciante rock 2000 2009 0 Moore 1 818738 Harmony Korine Steven Wilson rock 2000 2008 0 Moore 1 860986 The Dead Cant Testify Billy Talent rock 2000 2009 0 Moore 1 884504 The Lion Sleeps Tonight The Tokens pop 1960 1961 0 Moore 1 917077 The One That You Love Air Supply pop 1980 1981 0 Gardner 1 942428 If We Ever Meet Again Timbaland pop 2000 2009 0 Gardner 1 951005 So Serious Electric Light Orchestra pop 1980 1986 0 Gardner 1 953754 Eva Boudewijn de Groot pop 1960 1967 0 Gardner 1 989566 You Just May Be The One The Monkees pop 1960 1966 0 Gardner 1 991016 Blinking Lights For Me Eels pop 2000 2005 0

208

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Gardner 1 995982 La Nuit Je Mens Alain Bashung pop 1990 1998 0 Gardner 1 997590 Baby Justin Bieber pop 2010 2010 0 Gardner 1 999717 I’m Not In Love 10cc pop 1970 1975 0 Gardner 1 1021556 In Friends We Trust Chunk! No Captain rock 2010 2011 0 Chunk! Gardner 1 1036137 Blood In My Eyes Sum 41 rock 2010 2011 0 Gardner 1 1070831 Help Is On The Way Rise Against rock 2010 2011 0 Gardner 1 1095372 I Wish Stevie Wonder pop 1970 1976 0 Gardner 1 1097725 Say You’ll Haunt Me Stone Sour rock 2010 2010 0 Gardner 1 1113836 Aint Fit To Live Here Graveyard rock 2010 2011 0 Wood 1 1133188 One Thing One Direction pop 2010 2012 0 Wood 1 1141818 Quand On Na Que Lamour Jacques Brel pop 1950 1957 0 Wood 1 1141914 La Complainte De La Butte Patrick Bruel pop 2000 2003 0 Wood 1 1143365 See No Evil Television rock 1980 1977 0 Wood 1 1144262 Up All Night Slaughter rock 1990 1990 0 Wood 1 1149169 We Are So Fragile Gary Numan pop 1970 1979 0 Wood 1 1168312 Alpha Omega Architects rock 2010 2012 0 Wood 1 1179475 Save Me Gotye pop 2010 2011 0 Wood 1 1194568 Live While Were Young One Direction pop 2010 2012 0 Wood 1 1215446 Ties That Bind Alter Bridge rock 2000 2007 0 Wood 1 1243177 More Than This One Direction pop 2010 2012 0 Wood 1 1399746 How Can I Tell Her Lobo pop 1970 1973 0 Nichols 1 1416176 Riders On The Storm The Doors rock 1970 1971 0 Nichols 1 1453289 My Cherie Amour Stevie Wonder pop 1960 1969 0

209

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Nichols 1 1456126 Smoorverliefd Doe Maar pop 1980 1981 0 Nichols 1 1468533 Dreamland Express John Denver pop 1980 1985 0 Nichols 1 1470830 Fooling Yourself The Angry Young Man Styx rock 1970 1977 0 Nichols 1 1483165 From A Mountain In The Middle Of Panic! At the Disco pop 2000 2008 0 The Cabins Nichols 1 1504491 I’ll Fly For You Spandau Ballet pop 1980 1984 0 Nichols 1 1504645 More Than This Roxy Music pop 1980 1982 0 Nichols 1 1512237 Maps Maroon 5 pop 2010 2014 0 Shea 1 1699889 Photograph Ed Sheeran pop 2010 2014 0 Shea 1 1760606 Mummy Dust Ghost rock 2010 2015 0 Shea 1 1787990 Pusher Love Girl Justin Timberlake pop 2010 2013 0 Shea 1 1799965 Automatic Overdrive Slash rock 2010 2014 0 Nichols 1 2040750 I’m A Believer The Monkees pop 1960 1967 0 Nichols 1 2067353 Roll Over Beethoven The Beatles pop 1960 1963 0 Shea 1 2209991 Torso Of The Week Everything Everything pop 2010 2013 0 Shea 1 2470746 Hanno Ucciso Luomo Ragno 883 pop 1990 1992 0 Moore 1 216785 Joan Of Arc Leonard Cohen pop 1970 1971 0 Wood 1 394212 Honey Bee Stevie Ray Vaughan & rock 1980 1984 0 Double Trouble Gardner 0 937164 Too Drunk To Fuck Dead Kennedys rock 1980 1980 1 Moore 0 214285 Dime Que No Ricardo Arjona pop 1990 1998 1 Moore 0 214911 Johnny B Goode Chuck Berry rock 1950 1958 1 Moore 0 216364 Give Me One Reason Tracy Chapman rock 1990 1988 1 Moore 0 216605 Help The Poor B.B. King rock 1960 1961 1 Moore 0 217199 My Favorite Mistake Sheryl Crow rock 1990 1998 1

210

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Moore 0 218421 Raven Do As Infinity pop 2000 2000 1 Moore 0 218665 En Algun Lugar Duncan Dhu rock 1980 1987 1 Moore 0 219438 Dreams Fleetwood Mac rock 1970 1977 1 Moore 0 219454 The Chain Fleetwood Mac rock 1970 1977 1 Gardner 0 221005 Straight On Heart rock 1970 1978 1 Gardner 0 221600 Escape Enrique Iglesias pop 2000 2001 1 Gardner 0 223686 Nobody’s Home Avril Lavigne rock 2000 2004 1 Gardner 0 227615 One Of Us Joan Osborne rock 1990 1995 1 Gardner 0 228508 Ana Pixies rock 1990 1990 1 Gardner 0 228537 Letter To Memphis Pixies rock 1990 1991 1 Gardner 0 229475 Spotlight Kid Rainbow rock 1980 1981 1 Wood 0 235185 A Ma Place Zazie pop 2000 2003 1 Wood 0 361883 My City Was Gone The Pretenders rock 1980 1984 1 Wood 0 372270 Do You Remember Rock N Roll Radio Ramones rock 1980 1980 1 Wood 0 418564 Ligaya Eraserheads rock 1990 1993 1 Nichols 0 451205 Ich Bin Nich Ich Tokio Hotel pop 2000 2005 1 Nichols 0 469024 The Thrill Is Gone B.B. King rock 1960 1969 1 Nichols 0 472256 I Still Remember Bloc Party rock 2000 2007 1 Nichols 0 481618 Kreuzberg Bloc Party rock 2000 2007 1 Nichols 0 497824 Funkytown Lipps Inc. pop 1980 1980 1 Nichols 0 502311 Middle Of The Road The Pretenders rock 1980 1984 1 Shea 0 624477 QueÃÅ Vida La MiÃÅa Reik pop 2000 2005 1 Shea 0 625529 Picha Pie Parokya ni Edgar rock 1990 1999 1 Shea 0 662227 Yesterday Once More Carpenters pop 1970 1973 1

211

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 0 672629 Promised Land Chuck Berry rock 1960 1964 1 Gardner 0 689874 Weird Hilary Duff pop 2000 2004 1 Wood 0 710242 Barbie Girl Aqua pop 1990 1997 1 Nichols 0 734569 Saving All My Love For You Whitney Houston pop 1980 1985 1 Shea 0 735221 Greatest Love Of All Whitney Houston pop 1980 1985 1 Shea 0 752461 My Little Red Book Love rock 1960 1966 1 Shea 0 764459 Hot N Cold Katy Perry pop 2000 2008 1 Moore 0 791099 Stranger In Moscow Michael Jackson pop 1990 1995 1 Moore 0 815247 Apple Blossom The White Stripes rock 2000 2000 1 Moore 0 822173 Banquet Bloc Party rock 2000 2005 1 Moore 0 845118 Ds Michael Jackson pop 1990 1995 1 Moore 0 867117 Awake And Alive Skillet rock 2000 2009 1 Moore 0 887011 Just Like Jesse James Cher pop 1980 1989 1 Moore 0 898866 Long Live Rock N Roll Rainbow rock 1970 1978 1 Moore 0 901349 Un Par De Palabras Hombres G pop 1980 1986 1 Gardner 0 924524 Get Back Demi Lovato pop 2000 2008 1 Gardner 0 934944 Far Coheed and Cambria rock 2010 2010 1 Gardner 0 993453 Familiar Taste Of Poison Halestorm rock 2000 2009 1 Gardner 0 1008801 Cherry Bomb The Runaways rock 1970 1976 1 Gardner 0 1069321 I Wanna Go Britney Spears pop 2010 2011 1 Gardner 0 1072211 Does Your Mother Know ABBA pop 1970 1979 1 Gardner 0 1119496 Summer Night City ABBA pop 1970 1979 1 Wood 0 1165510 Nubes Caifanes rock 1990 1992 1 Wood 0 1178428 My Medicine The Pretty Reckless rock 2010 2010 1

212

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Wood 0 1190387 Son of A Preacher Man Dusty Springfield pop 1960 1969 1 Wood 0 1191576 You’re No Good Linda Ronstadt rock 1970 1974 1 Wood 0 1199423 Can’t Get You Off My Mind Lenny Kravitz rock 2000 1995 1 Wood 0 1200732 Sad Beautiful Tragic Taylor Swift pop 2010 2012 1 Wood 0 1227801 Away We Go Coheed and Cambria rock 2010 2012 1 Wood 0 1229322 Key Entity Extraction V Sentry The Coheed and Cambria rock 2010 2015 1 Defiant Nichols 0 1407050 Love Alive Heart rock 1970 1977 1 Nichols 0 1445955 PTY (Pretty Young Thing) Michael Jackson pop 1980 1982 1 Nichols 0 1446309 Here’s To Us Halestorm rock 2010 2012 1 Nichols 0 1446870 Off The Wall Michael Jackson pop 1970 1979 1 Nichols 0 1481093 Dirty Paws Of Monsters and Men rock 2010 2012 1 Nichols 0 1495443 At Last Etta James rock 1960 1960 1 Nichols 0 1507186 Love Never Felt So Good Michael Jackson pop 2010 2014 1 Moore 0 1806067 Un Misil En Mi Placard Soda Stereo rock 1980 1984 1 Wood 0 1874414 Freak Like Me Halestorm rock 2010 2012 1 Nichols 0 2067673 Only When I Sleep The Corrs pop 1990 1998 1 Shea 0 2075413 When Will I Be Loved Linda Ronstadt rock 1970 1974 1 Moore 0 214900 Take My Breath Away Berlin pop 1980 1986 1 Gardner 0 229441 Black Masquerade Rainbow rock 1990 1995 1 Gardner 0 230527 Evil Ways Santana rock 1960 1969 1 Gardner 0 232200 2 Become 1 Spice Girls pop 1990 1996 1 Shea 0 646970 Hurt Christina Aguilera pop 2000 2008 1 Shea 0 745544 I Just Cant Stop Loving You Michael Jackson pop 1980 1987 1

213

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 0 752934 The Kick Inside Kate Bush pop 1970 1978 1 Shea 0 761196 Rainy Days And Mondays Carpenters pop 1970 1971 1 Moore 0 813436 They Don’t Care About Us Michael Jackson pop 1990 1995 1 Moore 0 831828 Frozen Madonna pop 1990 1998 1 Moore 0 833037 La Playa La Oreja de Van Gogh pop 2000 2009 1 Moore 0 847308 Rock With You Michael Jackson pop 1970 1979 1 Moore 0 901803 Out Of The Dark Falco pop 1990 1998 1 Moore 0 922722 Hey Baby No Doubt pop 2000 2001 1 Gardner 0 979928 Nice And Slow Usher pop 1990 1997 1 Gardner 0 1111368 Price Tag Jessie J pop 2010 2011 1 Wood 0 1147375 Goodbye To Love Carpenters pop 1970 1972 1 Wood 0 1164549 Take Me Tonight Kim Wilde pop 1980 1982 1 Wood 0 1189470 Chiquitita ABBA pop 1970 1979 1 Wood 0 1194243 Atomic Blondie rock 1970 1979 1 Wood 0 1211589 Promises In The Dark Pat Benatar rock 1980 1981 1 Wood 0 1219672 Wild Ones Flo Rida pop 2010 2012 1 Nichols 0 1468797 Neon Lights Demi Lovato pop 2010 2013 1 Nichols 0 1517185 That Dont Impress Me Much Shania Twain pop 1990 1997 1 Nichols 0 1674057 Prayer In C Lilly Wood & The Prick rock 2010 2010 1 Shea 0 1707881 Hoochie Coochie Man Muddy Waters rock 1960 1968 1 Shea 0 1730570 Hang On To Your Love Sade pop 1980 1984 1 Shea 0 1730601 The Sweetest Taboo Sade pop 1980 1985 1 Shea 0 1738380 Lo Que Sangra La C‚àö‚à´pula Soda Stereo rock 1980 1988 1 Shea 0 1762555 My Heart Is Broken Evanescence rock 2010 2011 1

214

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 0 1769657 Kid The Pretenders rock 1980 1980 1 Shea 0 1799369 Seven Nation Army The White Stripes rock 2000 2003 1 Moore 0 1800994 If I Had A Heart Fever Ray pop 2000 2009 1 Gardner 0 1839360 Torn Natalie Imbruglia pop 1990 1997 1 Gardner 0 1841985 Little Red Corvette Prince pop 1980 1982 1 Wood 0 1874210 Need Your Love So Bad Fleetwood Mac rock 1960 1969 1 Wood 0 1974449 California Dreamin’ The Mamas & The Papas pop 1960 1966 1 Nichols 0 2052156 Me And Bobby Mcgee Janis Joplin rock 1970 1971 1 Shea 0 2068463 We Belong Together Ritchie Valens rock 1950 1959 1 Shea 0 2118827 Porque Te Vas Jeanette pop 1970 1976 1 Shea 0 2225279 Mad About You Hooverphonic pop 2000 1996 1 Shea 0 2355423 Smile Nat King Cole pop 1950 1954 1 Shea 0 2374609 Hold On Alabama Shakes rock 2010 2012 1 Shea 0 2488707 Its My Party Lesley Gore pop 1960 1963 1 Shea 0 2628342 Maybellene Chuck Berry rock 1950 1959 1 Moore 0 214064 Nobody’s Wife Anouk rock 1990 1998 0 Moore 0 214625 Weak And Powerless A Perfect Circle rock 2000 2003 0 Moore 0 214860 Jive Talkin’ Bee Gees pop 1970 1975 0 Moore 0 215191 War Pigs Black Sabbath rock 1970 1975 0 Moore 0 215852 Ne Me Quitte Pas Jacques Brel pop 1950 1959 0 Moore 0 216788 Suzanne Leonard Cohen pop 1960 1968 0 Moore 0 217286 How The Gods Kill Danzig rock 1990 1992 0 Gardner 0 221667 Are You In Incubus rock 2000 2009 0 Gardner 0 222544 Candle In The Wind Elton John rock 1970 1973 0

215

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Gardner 0 223036 Epitaph King Crimson rock 1960 1969 0 Gardner 0 223224 Watchin’ You KISS rock 1970 1974 0 Gardner 0 223974 Nookie Limp Bizkit rock 1990 1999 0 Gardner 0 224882 Now And Forever Richard Marx pop 1990 1994 0 Gardner 0 225730 No Cigar Millencolin rock 2000 2000 0 Gardner 0 227626 Crazy Train Ozzy Osbourne rock 1980 1980 0 Gardner 0 229690 Round And Round Ratt rock 1980 1984 0 Gardner 0 232400 Just Looking Stereophonics rock 1990 1999 0 Wood 0 232437 Maggie May Rod Stewart rock 1970 1971 0 Wood 0 233943 I Wanna Rock Twisted Sister rock 1980 1984 0 Wood 0 234757 El Scorcho Weezer rock 1990 1996 0 Wood 0 236775 Tribute Tenacious D rock 2000 2002 0 Wood 0 238676 Stay Faraway So Close U2 pop 1990 1993 0 Wood 0 245246 Chanson Pour Lauvergnat Georges Brassens pop 1950 1955 0 Wood 0 335155 Niki Fm Hawthorne Heights rock 2000 2004 0 Wood 0 372988 The Last Time The Rolling Stones rock 1960 1965 0 Wood 0 374490 My Favourite Game The Cardigans rock 1990 1998 0 Nichols 0 437640 Getting Better The Beatles rock 1960 1967 0 Nichols 0 438088 Sunshine Of Your Love Cream rock 1960 1967 0 Nichols 0 445083 Harder Faster W.A.S.P. rock 1980 1987 0 Nichols 0 471885 Stuck In The Middle With You Stealers Wheel rock 1970 1972 0 Nichols 0 475372 Wonderful World James Morrison pop 2000 2006 0 Nichols 0 518394 Anthem Part Two Blink-182 rock 2000 2001 0 Nichols 0 540191 Lips Of An Angel Hinder rock 2000 2005 0

216

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Nichols 0 554368 Schism Tool rock 2000 2001 0 Nichols 0 558062 Blackest Eyes Porcupine Tree rock 2000 2002 0 Shea 0 571147 Jailhouse Rock Elvis Presley rock 1950 1957 0 Shea 0 579680 Stone Free Jimi Hendrix rock 1960 1967 0 Shea 0 593454 Jenny Wren Paul McCartney pop 2000 2005 0 Shea 0 602817 Those Were The Days Cream rock 1960 1968 0 Shea 0 641929 Riff Raff AC\/DC rock 1970 1978 0 Wood 0 712985 Honestly Stryper rock 1980 1986 0 Moore 0 781307 Video Killed The Radio Star Buggles pop 1970 1979 0 Moore 0 809094 Getting’ Better Tesla rock 1980 1986 0 Moore 0 832886 Growing Old Is Getting Old Silversun Pickups rock 2000 2009 0 Moore 0 855742 I Guess That’s Why They Call It The Elton John pop 1980 1983 0 Blues Moore 0 859582 Venus In Furs The Velvet Underground rock 1960 1967 0 Moore 0 870518 Sunshine Superman Donovan rock 1960 1966 0 Moore 0 889294 Beer Reel Big Fish rock 1990 1996 0 Moore 0 902002 Help Is On Its Way Little River Band rock 1970 1977 0 Moore 0 919570 Rockstar Nickelback rock 2000 2005 0 Gardner 0 934385 Find My Way Back Four Year Strong rock 2010 2010 0 Gardner 0 945257 Dancing With The Moonlit Knight Genesis rock 1970 1973 0 Gardner 0 972983 Im Not Your Steppin Stone The Monkees pop 1960 1967 0 Gardner 0 974666 Listen To The Band The Monkees pop 1960 1969 0 Gardner 0 1066477 Night Songs Cinderella rock 1980 1986 0 Wood 0 1127803 Somebody That I Used To Know Gotye pop 2010 2011 0

217

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Wood 0 1136524 I’m Not A Vampire Falling In Reverse rock 2010 2011 0 Wood 0 1141424 South City Midnight Lady The Doobie Brothers rock 1970 1973 0 Wood 0 1147550 Bully Shinedown rock 2010 2012 0 Wood 0 1162065 Just My Imagination The Cranberries rock 1990 1999 0 Wood 0 1217075 The Piano Knows Something I Don’t Panic! At the Disco pop 2000 2008 0 Know Wood 0 1240930 Sonic Reducer Dead Boys rock 1970 1977 0 Nichols 0 1417282 Arabella Arctic Monkeys rock 2010 2013 0 Nichols 0 1428509 Love On A Farmboy’s Wages XTC pop 1980 1983 0 Nichols 0 1480276 Sing Ed Sheeran pop 2010 2014 0 Nichols 0 1491471 Here Today The Beach Boys rock 1960 1966 0 Nichols 0 1504500 Love Foolosophy Jamiroquai pop 2000 2001 0 Shea 0 1682137 Rock Or Bust AC/DC rock 2010 2014 0 Shea 0 1686768 Crazy Vibes Selah Sue pop 2010 2012 0 Shea 0 1703940 Save Today Seether rock 2010 2014 0 Shea 0 1744603 Friday Im In Love The Cure rock 1990 1992 0 Moore 0 1815572 Heavy Cloud No Rain Sting pop 1990 1993 0 Wood 0 1867562 Wasted On The Way Crosby Stills & Nash pop 1980 1982 0 Wood 0 1906728 Crows On A Wire Alter Bridge rock 2010 2016 0 Wood 0 1977355 Everybody’s Talkin Harry Nilsson pop 1960 1968 0 Nichols 0 2018996 Fire Woman The Cult rock 1980 1989 0 Nichols 0 2060571 No Face No Name No Number Modern Talking pop 2000 1999 0 Nichols 0 2066191 California Girls The Beach Boys pop 1960 1965 0 Shea 0 2227761 The Land Of Make Believe The Moody Blues pop 1970 1972 0

218

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Shea 0 2401679 Pleasant Valley Sunday The Monkees pop 1960 1967 0 Moore 0 216277 Unsung Vanessa Carlton pop 2000 2002 0 Moore 0 219122 Mutha Don’t Wanna Go To School Extreme rock 1980 1989 0 Today Gardner 0 223814 The Lemon Song Led Zeppelin rock 1960 1969 0 Gardner 0 228951 Lazing On A Sunday Afternoon Queen rock 1970 1975 0 Wood 0 339536 Incomplete Backstreet Boys pop 2000 2005 0 Wood 0 377348 Mr. Blue Sky Electric Light Orchestra pop 1970 1977 0 Nichols 0 518616 Golden Brown The Stranglers rock 1980 1981 0 Shea 0 601049 Zzyzx Rd Stone Sour rock 2000 2006 0 Wood 0 720004 As Long As You Love Me Backstreet Boys pop 1990 1999 0 Shea 0 744135 Death And All His Friends Coldplay pop 2000 2008 0 Shea 0 755962 Oud En Afgedankt Marco Borsato pop 1990 1996 0 Moore 0 837425 42 Coldplay pop 2000 2008 0 Moore 0 856685 Love Is All Around Wet Wet Wet pop 1990 1994 0 Moore 0 858361 The One Elton John pop 1990 1992 1 Moore 0 918761 Strut Adam Lambert pop 2010 2009 1 Gardner 0 982076 Blessed Elton John pop 1990 1995 0 Gardner 0 1001104 Show Me The Meaning Of Being Lonely Backstreet Boys pop 1990 1999 0 Gardner 0 1033017 Down To Earth Justin Bieber pop 2000 2009 0 Gardner 0 1053023 Holiday Bee Gees rock 1960 1967 0 Gardner 0 1100078 Couleur Cafe Serge Gainsbourg pop 1960 1964 0 Wood 0 1120047 Pumped Up Kicks Foster the People pop 2010 2011 0 Nichols 0 1399772 Knee Deep Zac Brown Band rock 2010 2010 0

219

Appendix B continued Annotator Test GP ID Song Artist Style Decade album year Diverse Nichols 0 1482574 Cabin Essence The Beach Boys pop 1960 1966 0 Nichols 0 1675887 Faith George Michael pop 1990 1987 0 Shea 0 1712585 To Be Free Simply Red pop 1990 1985 0 Shea 0 1732925 Let It Burn The Orwells rock 2010 2014 0 Moore 0 1838384 Feet For Hands Everything Everything pop 2010 2013 0 Gardner 0 1853763 Throwing It All Away Genesis rock 1980 1986 0 Wood 0 1861963 Ful Stop Radiohead pop 2010 2016 0 Wood 0 1866253 Left Alone Blink-182 rock 2010 2016 0 Wood 0 1916945 Wichita Lineman Glen Campbell pop 1960 1968 0 Nichols 0 2039665 Cough Cough Everything Everything pop 2010 2013 0 Nichols 0 2051274 Last Kiss J. Frank Wilson and The pop 1960 1964 0 Cavaliers Shea 0 2217511 Saturnz Barz Gorillaz pop 2010 2017 0 Shea 0 2435003 Signed Sealed Delivered Im Yours Stevie Wonder pop 1970 1970 0 Shea 0 2771509 Help Me Rhonda The Beach Boys pop 1960 1965 0 Shea 0 2791567 Don’t Try Everything Everything pop 2010 2013 0

All form annotations are available at (sheatheory.com/pop-rock-performance-corpus).

220

Appendix C:

Performance Data from Motion-capture Experiment

Each graph represents x-axis and y-axis changes in pixel distance over time by participant. The grey vertical bars represent moments (1.5 seconds) of transition. Pop 90 bpm

221

Appendix C continued, Pop 90 bpm

Rock 90 bpm

222

Appendix C continued, Rock 90 bpm

223

Appendix C continued, Pop 120 bpm

224

Appendix C continued, Rock 120 bpm

225

Appendix C continued, Rock 120 bpm

Hi-resolution images, data and code are available at (sheatheory.com/mocap).

226