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⁵ This research is supported by AHRC grant AH/N004663/1. The authors are grateful to Dan Hulme for his expert technical advice and assistance.

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⁸ Galkin, A History of Orchestral Conducting.

⁹ See Cayenna Ponchione-Bailey, ‘Tracking Authorship and Creativity in Orchestral Performance’ (DPhil diss., University of Oxford, 2016).

¹⁰ Since the original submission of this article, we have used the suite of research methods detailed here to collect data from a professional orchestra of string players working on repertoire by Fuchs and Tchaikovsky. The ensemble, Accordes!, comprised performers specializing in nineteenth-century historical practices, drawn together by the ‘Transforming Nineteenth-Century Historically Informed Practice’ research project. Led by the project's Principal Investigator and violinist, Claire Holden, Accordes! explored expressive asynchrony alongside other late nineteenth-century stylistic features by experimenting with the distribution of individual agency within the group. The findings from that project will be published in forthcoming chapters and articles.

¹¹ For example, Binet, Alfred and Courtier, Jules, ‘Recherches graphiques sur la musique’, L'année Psychologique 2 (1895): 201–22CrossRefGoogle Scholar; Seashore, Carl, Psychology of Music (New York: McGraw Hill, 1938)Google Scholar; Shaffer, L. Henry, ‘Performances of Chopin, Bach, and Bartok: Studies in Motor Programming’, Cognitive Psychology 13/3 (1981): 326–76CrossRefGoogle Scholar.

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¹³ Rasch, ‘Synchronization’, 131.

¹⁴ Examples are Shaffer, L. Henry, ‘Timing in Solo and Duet Piano Performances’, Quarterly Journal of Experimental Psychology 36/4 (1984): 577–95CrossRefGoogle Scholar; Goodman, Elaine, ‘Ensemble Performance’, in Musical Performance: A Guide to Understanding, ed. Rink, John (Cambridge: Cambridge University Press, 2002): 153–67CrossRefGoogle Scholar; Davidson, Jane W. and Good, James M. M., ‘Social and Musical Co-ordination Between Members of a String Quartet: An Exploratory Study’, Psychology of Music 30/2 (2002): 186–201CrossRefGoogle Scholar; Williamon, Aaron R. and Davidson, Jane W., ‘Exploring Co-performer Communication’, Musicae Scientiae 6/1 (2002): 53–72CrossRefGoogle Scholar; Goebl, Werner and Palmer, Caroline, ‘Synchronization of Timing and Motion Among Performing Musicians’, Music Perception 26/5 (2009): 427–38CrossRefGoogle Scholar; and Timmers, Renee, Endo, Satoshi, Bradbury, Adrian and Wing, Alan M., ‘Synchronization and Leadership in String Quartet Performance: A Case Study of Auditory and Visual Cues’, Frontiers in Psychology 5 (2014): 645, DOI=10.3389/fpsyg.2014.00645CrossRefGoogle ScholarPubMed. See also Bishop, Laura and Goebl, Werner, ‘Beating Time: How Ensemble Musicians’ Cueing Gestures Communicate Beat Position and Tempo’, Psychology of Music 46/1 (2018): 84–106CrossRefGoogle ScholarPubMed, for an account of the spatio-temporal properties of cueing gestures in same and different instrument duos (violin and piano).

¹⁵ A review of the mechanical and electrical devices employed for measuring performance parameters including timing can be found in Goebl, Werner, Dixon, Simon, De Poli, Giovanni, Friberg, Anders, Bresin, Robert, and Widmer, Gerhard, ‘“Sense” in Expressive Music Performance: Data Acquisition, Computational Studies, and Models’, in Sound to Sense – Sense to Sound: A State of the Art in Sound and Music Computing, ed. Polotti, Pietro and Rocchesso, Davide (Berlin: Logos, 2008): 159–242Google Scholar.

¹⁶ Chris Cannam, Christian Landone and Mark Sandler, ‘Sonic Visualiser: An Open Source Application for Viewing, Analysing, and Annotating Music Audio Files’, Proceedings of the ACM Multimedia 2010 International Conference, 25–29 October 2010, Florence, Italy. Available at www.sonicvisualiser.org/sv2010.pdf. The public domain application is available at www.sonicvisualiser.org/.

¹⁷ Goebl, Werner, Dixon, Simon and Schubert, Emery, ‘Quantitative Methods: Motion Analysis, Audio Analysis, and Continuous Response Techniques’, in Empirical Approaches Across Styles and Cultures: Expressiveness in Music Performance, ed. Fabian, Dorottya, Timmers, Renee and Schubert, Emery (Oxford: Oxford University Press, 2014): 226Google Scholar.

¹⁸ Richard Polfreman, ‘Comparing Onset Detection and Perceptual Attack Time’, in Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013), ed. Alceu de Souza Britto Junior, Fabien Gouyon and Simon Dixon (International Society for Music Information Retrieval, 2013): 523–8.

¹⁹ For string instruments, for example, the gauge, mass, length and tension of the string will significantly affect its behaviour (violins and double basses, for example, have very different characteristics), as will different bow strokes and whether a note is defined by a finger change, a slide, a bow stroke or combinations of all three.

²⁰ Polfreman, ‘Comparing Onset Detection'.

²¹ Matthew Wright proposes that perceptual attack time is better considered a probability density function, since the characteristics of specific sounds, such as the sharpness of their attacks, will mean that different individuals and even individuals making repeated judgments about the same note onset will find a range of values that sound equally correct. See Matthew Wright, ‘The Shape of an Instant: Measuring and Modeling Perceptual Attack Time with Probability Density Functions’, (PhD diss., Stanford University, 2008): iv.

²² Murnighan, J. Keith and Conlon, Donald E., ‘The Dynamics of Intense Work Groups: A Study of British String Quartets’, Administrative Science Quarterly 36 (1991): 165–86CrossRefGoogle Scholar; Davidson and Good, ‘Social and Musical Co-ordination’; King, Elaine, ‘The Roles of Student Musicians in Quartet Rehearsals’, Psychology of Music 34/2 (2006): 262–82CrossRefGoogle Scholar; Seddon, Frederick, ‘Modes of Communication During Jazz Improvisation’, British Journal Of Music Education 22/1 (2005): 47–61CrossRefGoogle Scholar; Blank, Marilyn and Davidson, Jane W., ‘An Exploration of the Effects of Musical and Social Factors in Piano Duo Collaborations’, Psychology of Music 35/2 (2007): 231–48CrossRefGoogle Scholar; Seddon, Frederick and Biasutti, Michele, ‘A Comparison of Modes of Communication Between Members of a String Quartet and a Jazz Sextet’, Psychology Of Music 37/4 (2009): 395–415CrossRefGoogle Scholar; McCaleb, J. Murphy, Embodied Knowledge in Ensemble Performance (Farnham: Ashgate, 2014)Google Scholar.

²³ For example, Murnighan and Conlon, ‘The Dynamics of Intense Work Groups’.

²⁴ See Clarke, Eric F., Doffman, Mark and Lim, Liza, ‘Distributed Creativity and Ecological Dynamics: A Case Study of Liza Lim's “Tongue of the Invisible”’, Music & Letters 94 (2013): 628–63CrossRefGoogle Scholar; Bayley, Amanda, ‘Ethnographic Research Into Contemporary String Quartet Rehearsal and Performance’, Ethnomusicology Forum 20/3 (2011): 385–411CrossRefGoogle Scholar.

²⁵ VSR uses video recordings of participants’ own activities to prompt recollections of their thought process and experiences during a specific task. The method has been used since the early 1980s to study cognitive processes in naturalistic environments. It is particularly useful for reflecting on activities that involve high levels of concentration, absorption or ‘flow’ which limit a participant's ability to provide commentary during the activity (such as speak aloud protocols), or to recall details of the event without an external prompt. See Lyle, John, ‘Stimulated Recall: A Report on Its Use in Naturalistic Research’, British Educational Research Journal 29/6 (2003): 861–78CrossRefGoogle Scholar.

²⁶ Davidson and Good, ‘Social and Musical Co-ordination’; Seddon, Frederick A. and Biasutti, Michele, ‘Modes of Communication Between Members of a String Quartet’, Small Group Research 40/2 (2009): 115–37CrossRefGoogle Scholar. VSR has also been used in music research to investigate individuals’ experiences of creativity in one-to-one conservatoire music lessons (see James, Mirjam, Wise, Karen J. and Rink, John, ‘Exploring Creativity in Musical Performance Through Lesson Observation with Video-Recall Interviews’, Scientia Paedagogica Experimentalis 47/2 (2010): 219–50Google Scholar) and the creative thought processes of conductors and composers during composition or rehearsal (see Donin, Nicolas and Féron, François-Xavier, ‘Tracking the Composer's Cognition in the Course of a Creative Process: Stefano Gervasoni and the Beginning of Gramigna’, Musicae Scientiae 16/3 (2012): 262–85CrossRefGoogle Scholar).

²⁷ See Faulkner, Robert, ‘Orchestra Interaction: Some Features of Communication and Authority in an Artistic Organization’, Sociological Quarterly 14/2 (1973): 147–57CrossRefGoogle Scholar; Atik, Yaakov, ‘The Conductor and the Orchestra: Interactive Aspects of the Leadership Process’, Leadership and Organization Development Journal 15/1 (1994): 22–8CrossRefGoogle Scholar; Koivunen, Niina, Leadership in Symphony Orchestras: Discursive and Aesthetic Practices (Tampere: Tampere University Press, 2003)Google Scholar; Hunt, James, Stelluto, George and Hooijberg, Robert, ‘Toward New-Wave Organization Creativity: Beyond Romance and Analogy in the Relationship Between Orchestra-Conductor Leadership and Musician Creativity’, The Leadership Quarterly 15 (2004): 145–62CrossRefGoogle Scholar; Boerner, Sabine and von Streit, Christian Freiherr, ‘Transformational Leadership and Group Climate – Empirical Results from Symphony Orchestra’, Journal of Leadership and Organizational Studies 12/3 (2005): 31–41CrossRefGoogle Scholar; D'Ausilio, Alessandro, Badino, Leonardo, Li, Yi, Tokay, Sera, Craighero, Laila, Canto, Rosario, Aloimonos, Yiannis and Fadiga, Luciano, ‘Leadership in Orchestra Emerges from the Causal Relationships of Movement Kinematics’, Plos One 7/5 (2012): e35757CrossRefGoogle ScholarPubMed.

²⁸ See, for example, Khodyakov, D.M., ‘The Complexity of Trust-Control Relationships in Creative Organizations: Insights from a Qualitative Analysis of a Conductorless Orchestra’, Social Forces 86/1 (2007): 1–22CrossRefGoogle Scholar; Leslie Lewis, ‘The Incomplete Conductor: Theorizing the Conductor's Role in Orchestral Interpretation in the Light of Shared Leadership Practices’ (PhD diss., Royal Holloway University of London, 2012).

²⁹ Dobson, Melissa and Gaunt, Helen, ‘Musical and Social Communication in Expert Orchestral Performance’, Psychology Of Music 43/1 (2015): 24–42CrossRefGoogle Scholar.

³⁰ Clarke, Doffman and Lim, ‘Distributed Creativity and Ecological Dynamics’.

³¹ Ponchione-Bailey, ‘Tracking Authorship and Creativity’.

³² Langer, Ellen, Russell, Timothy and Eisenkraft, Noah, ‘Orchestral Performance and the Footprint of Mindfulness’, Psychology of Music 37/2 (2008): 125–36CrossRefGoogle Scholar.

³³ Ponchione-Bailey, Cayenna, ‘The Body Orchestral: The Embodied Process of Orchestral Performance’, in Collaborative and Distributed Processes in Contemporary Music-Making, ed. Redhead, Lauren and Glover, Richard (Newcastle: Cambridge Scholars, 2018): 66–83Google Scholar.

³⁴ Cayenna Ponchione-Bailey, ‘Tracking Authorship and Creativity’.

³⁵ www.socrative.com/. The Socrative app allowed us to capitalize on mobile phone technology and the ease and speed at which our student participants were able to type on internet-connected smart phones. Participants logged into Socrative anonymously, but identified their orchestral position (e.g. Violin II-3, indicating outside player of second desk of second violins), thus preserving their anonymity while allowing the analysis of their data to be sensitive to orchestral position.

³⁶ Players who did not have a smartphone with them at the workshop gave their responses using hard copy equivalents. 90 per cent of responses were collected via the smartphone app.

³⁷ There are three reasons for this focus: 1) the central role of string sections within orchestras; 2) the lack of research on string section sound; and 3) the number of inputs in the audio interfaces available for us to use for this pilot study.

³⁸ The annotator for the data reported in this article was the first author, who has 20 years of experience as an orchestral percussionist and conductor.

³⁹ The authors gratefully acknowledge the contribution of Graeme Bailey in the Computer Science Department at Cornell University for writing the program necessary to process the data set.

⁴⁰ The calculation deliberately takes no account of which instruments are first and last. Thus, the first onset could be a violin I and the last a viola (at a metrical position where violins and violas are playing); or at other positions (where only one instrumental section happens to have a note) the first and last onsets could be from within the same instrumental section.

⁴¹ These differences are only indicative since an analysis shows that there is no statistical difference between the average ranges of the conditions.

⁴² The standard deviation captures the variability of the values within the data set.

⁴³ Rasch, ‘Synchronization’.

⁴⁴ As a comparison, the semiquaver played at metrical position (d) in C2 has a theoretical duration of approximately 200msec.

⁴⁵ Six-point scales prevent respondents from using a non-committal middle value.

⁴⁶ In technical terms, Wilks’ lambda (the MANOVA test statistic) had a value of 0.283 (indicating that 72% of the variance was due to the four conditions), which corresponds to F (23, 66) = 3.77; p<0.0001 (an F-ratio of 3.77 with 23 and 66 degrees of freedom, and a probability [significance level] of less than 0.0001 – i.e. highly significant).

⁴⁷ Analysis of variance (ANOVA) is a standard statistical method for evaluating the changes caused by three or more conditions on the value of a variable.

⁴⁸ Care needs to be taken in attributing too much to the size of the F-ratio, which is influenced by a number of factors. However, since we are dealing with a within-subjects design (all participants in the study evaluated all conditions), with no missing data, it is reasonable to make heuristic use of the size of the F-ratio to indicate broadly stronger and weaker effects.

⁴⁹ Dobson and Gaunt, ‘Musical and Social Communication’; Ponchione-Bailey ‘Tracking Authorship and Creativity’.

⁵⁰ There are some interesting consequences here for the development of orchestral players – to be explored elsewhere. In brief, the players’ perception that C1 was ‘orchestra as usual’ and that C3 presented greater ensemble challenges because it required listening to colleagues and playing more like a chamber ensemble illuminates a gap between students’ experiences of playing in youth or conservatoire orchestras and the demands of professional orchestral performance.

⁵¹ See Clarke, ‘The Impact of Recording’.

⁵² Langer, Russell and Eisenkraft, ‘Orchestral Performance’.

⁵³ MERID (Media Enabled Research Interface and Database) was developed by students at Cornell University. See Ponchione-Bailey, ‘Tracking Authorship and Creativity’.

⁵⁴ The Schulich and Max Planck facilities allow audience members to send continuous responses on a considerable range of dimensions, and in response to all manner of performance features, via tablet technology wired into the auditorium.

⁵⁵ Shaffer, ‘Performances of Chopin, Bach, and Bartok’.