Book Chapter
Reference
The resilience approach to studying group interaction in music ensemble
GLOWINSKI, Donald, et al.
GLOWINSKI, Donald, et al. The resilience approach to studying group interaction in music ensemble. In: The Routledge companion to embodied music interaction. Routledge, 2017.
Available at:
http://archive-ouverte.unige.ch/unige:151017
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RESILIENCE IN MUSIC ENSEMBLE 3
4 5
Title:
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The Resilience Approach to Studying Group Interaction in Music Ensemble 7
Donald Glowinski1, Fabrizio Bracco2, Carlo Chiorri2, Didier Grandjean1 8
1Swiss Center for Affective Sciences and Faculty of Psychology and Educational Sciences, 9
NEAD, University of Geneva, Geneva, Geneva, Switzerland 10
2Disfor, Department of Education Sciences, University of Genoa, Italy 11
12
Abstract 13
We propose resilience as a framework for the understanding of group processes in music 14
ensemble. Music ensemble has many properties of a resilient system, as it can adjust its 15
functioning to changes and disturbances and sustain required operations under a variety of 16
conditions. This capacity is achieved by means of social and cognitive competencies, as well as 17
related skills. The chapter describes the strategies developed by musicians at various levels of 18
expertise to achieve coordination even under conditions of uncertainty, and reveals the 19
compromise achieved by experts between risk-taking attitudes and the capacity to cope with 20
internal and external perturbations.
21
Keywords: Music ensemble, resilience, nonverbal communication 22
23
Music ensemble as a resilient system 24
25
Introduction 26
An emerging line of research considers the music ensemble (e.g., string quartets, 27
symphonic orchestras) as a valuable test case for studying social interactions. Music ensembles 28
indeed offer a unique variety of scenarios that differ in terms of social complexity (from duo to 29
symphonic orchestra), participants’ expertise (from beginner to advanced musicians), and 30
musical structure complexity (from simple to highly complex musical structures). All of these 31
factors can affect the way in which the interactions occur. In addition, the music ensemble allows 32
an experimenter to evaluate the many channels of communication through which people can 33
coordinate with one another and together achieve joint objectives (e.g., verbal exchange, 34
nonverbal body expressivity; D’Ausilio, Novembre, Fadiga, & Keller, 2015). In such dynamic 35
joint actions—which are both complex and demanding—musicians also have to cope with their 36
own emotions and feelings, which are induced during the performances by the musical aspects 37
and social interactions.
38
Somewhat surprisingly, music ensemble has recently been used as a metaphor for the 39
organizational issues that are typical of business environments (Gilboa & Tal-Shmotkin, 2010).
40
For example, the four musicians of a string quartet can be seen as a typical implementation of 41
team self-management, in which all participants share a similar responsibility in achieving group 42
objectives. The advantage of applying the conceptual apparatus of a business organization to 43
music is twofold: first, it enables one to revisit social interaction processes in music by using 44
elements that do not exclusively pertain to the music field, but may affect the musical process 45
(e.g., nonverbal communication, hierarchy, emotion regulation); second, analysis of social and 46
individual behavior from a broader view facilitates the identification of commonalities between 47
music and extra-musical cases or, in contrast, helps identify a music case in terms of human 48
organization or joint activity. Supporting this multidisciplinary perspective, our approach aims to 49
apply the resilience concept inherited from the field of industrial safety (Hollnagel, 2011) to the 50
music ensemble case. We suggest that this concept of resilience can explain the ability of 51
musicians to adapt to external or internal perturbations, which affords them with the ability to 52
anticipate future events. The observed behavior in the studies reviewed in the present chapter has 53
not been explicitly considered as part of a resilience approach, as the hypotheses and measures 54
relate to other theoretical backgrounds (e.g., motor simulation, joint action; Sebanz & Knoblich, 55
2009). Our purpose, however, is to show how the resilience approach can help researchers to 56
consider implicit relationships between these variables and behaviors that would otherwise be set 57
apart, as well as how such relationships may be useful in understanding how individuals and 58
groups succeed in managing unexpected perturbations. The chapter comprises three sections.
59
The first introduces domain-general aspects of the resilience approach and eventually focuses on 60
music-specific issues. The second section describes the resilience framework and how it could be 61
applied to music ensemble performance. Finally, in the third section, we propose to apply the 62
resilience approach in order to revisit the results of recent empirical studies within this novel 63
framework.
64 65
Music ensemble as a resilient system 66
The concept of resilience, originally derived from mechanical engineering, has been 67
adapted to organizational studies after having worked its way through ecology (Holling, 1973) 68
and psychology (Hughes, 2012). It deals with the capability of a system to maintain a certain 69
degree of integrity (i.e., “to survive”) when perturbed by a significant shock, internal or external.
70
More precisely, the ecologist Crawford Holling (1973, p. 14) defined resilience as a “measure of 71
the persistence of systems and of their ability to absorb change and disturbance and still maintain 72
the same relationships between populations or state variables.” Note that such a system not only 73
can maintain “the same relationships between populations or state variables” (Holling, 1973, p.
74
14), but it can also adapt or cope with changes in a dynamic way, challenging the complex joint 75
actions with a high temporal resolution.
76
Moving from ecology to complex system engineering, this concept has been adopted to 77
explain both a pure reactive capability of the system to adapt to external perturbations and a 78
more proactive attitude that can afford the ability to anticipate future events, that is, the capacity 79
to perform predictive coding and the related adjustment processes (Summerfield & de Lange, 80
2014). In addition, the capacity of a system to balance stability and variability has been 81
extensively investigated in dynamic system theories that model social coordination dynamics 82
(Schmidt & Richardson, 2008). This view is the philosophical core of resilience engineering, in 83
which resilience has been defined as the system’s ability to absorb unexpected perturbations 84
(Hollnagel, Woods, & Leveson, 2006). Music ensemble shares many properties of a resilient 85
system, as “it can adjust its functioning prior to, during, or following events (changes, 86
disturbances, and opportunities), and thereby sustain required operations under both expected 87
and unexpected conditions” (Hollnagel et al., 2011, p. xxxvi). When the system operates in a 88
highly perturbed environment (e.g., emergency operators, or a jazz quartet involved in 89
improvisation), the “safe” and effective performance is based on members’ skills in continuously 90
readjusting their performance according to the ongoing situation. At this level, individual and 91
team skills are fundamental for the resilient performance (Amalberti, 2013). Consider, for 92
example, how the four musicians of a string quartet adapt to each other’s behaviors to produce a 93
unified, homogeneous, and remarkable performance when faced with the unexpected 94
perturbation of a noisy audience. Consider also the orchestra director who faces up to 130 95
musicians in a symphonic orchestra and must synchronize them, share musical objectives, and 96
lead them to behave as a unique and complex organism. In our opinion, these musical cases can 97
be compared to some extent to other social situations, such as a group of practitioners in an 98
emergency situation, in which coordination is necessary within compelling time constraints.
99
Therefore, being resilient in a music ensemble means dynamically adapting to the perturbations 100
as a result of the proper response of musicians as individuals and as a team.
101
The added value that the notion of resilience brings is to consider the individual and 102
social challenges of playing within a music ensemble together and to specifically detail the role 103
of soft skills (Wachs, Weber Righi, & Saurin, 2012). Each individual in a music ensemble must 104
find a moment-by-moment balance between their own expressive objective and the necessity to 105
reach a collective solution that satisfies the entire group and produces an original and remarkable 106
global musical performance. A realm of research in which we participated also separately 107
investigated individual emotional skills through self-report (Davidson, 2012), musically-related 108
technical competences (Keller, Dalla Bella, & Koch, 2010), or collective organizational 109
processes (e.g., level of coordination) by using automatic behavior analysis (Glowinski et al., 110
2013). Little research has been done, however, to correlate these individual and group emotional 111
levels, or to understand the group capacity to achieve common objectives and to cope with 112
external difficulties together.
113
In order to clarify the additional value of the resilience approach in existing theories in 114
psychology as applied to music interaction, we selected the framework developed by Keller 115
(2014) and the theory of flow (Nakamura, & Csikszentmihalyi, 2014). Keller has provided a 116
general framework for studying music ensemble that integrates various psychological 117
mechanisms to explain the capacity of musicians to share aesthetic objectives through well-tuned 118
body coordination and social interaction. This model does not, however, provide details about 119
the regulatory strategies that musicians may enact during their performances and, specifically, 120
the processes and skills to manage unexpected situations. Beyond a mere descriptive approach 121
and yet useful typology of the mechanisms used in music interaction provided by Keller, the 122
resilience approach we developed provides a dynamic and integrative view of the type of 123
perturbations and the relevant skill levels used to handle such perturbations at the individual and 124
the group level. In addition, our model can describe the transition steps needed to move from one 125
skill to another that, as a whole, gives our approach a unique explanatory and predictive power.
126
Applied to various aspects of music performance (e.g., Wrigley & Emmerson, 2013), the 127
theory of flow developed by Csikszentmihalyi (1975) describes the flow state that results from 128
an optimal balance between the challenge posed by the situation and the skills of the person 129
managing the task. Whereas Csikszentmihalyi’s approach is mainly descriptive and defines in 130
extenso all the characteristics (e.g., having clear objectives, total focus on the task at hand, loss 131
of self-awareness, loss of time awareness), it does not detail the processes and the cognitive, 132
emotional, and social skills necessary to return to the flow state and ensure a resilient 133
performance.
134
The resilience model that we describe in the next section is not an alternative to the 135
above-mentioned theories and models. Rather, it is an advance in detailing the skills and 136
dynamics behind an effective music performance in the presence of perturbations. Therefore, the 137
resilience approach has the advantages of having good predictive power, being able to be 138
adopted as a heuristic framework, and providing clear hypotheses on how individual skills and 139
group properties must be combined to efficiently handle perturbations.
140 141
The resilience framework as a model for resilient performance 142
During a musical performance, perturbation is not always present, but, when it happens, 143
it is important for the team to provide a quick and coherent response. This is a process that has 144
considerable costs in terms of cognitive resources. To systematically approach the way in which 145
musicians retrieve their cognitive resources at the individual and the team level, we refer to the 146
Skill-Rule-Knowledge (SRK) model by Rasmussen (1983). This model states that when 147
individuals perform a routine activity, they rely on automated, overlearned processes and on 148
procedural memory (Graybiel, 2008). This is the skill-based level. When performers face an 149
unexpected event, they move a step higher in the cognitive ladder and carefully follow the 150
execution rules. This is the rule-based level. When the rules are not enough and the perturbation 151
is even stronger, the performer has to move a further step to the top level of the cognitive ladder 152
and engage in effortful attentional processes, the so-called knowledge-based level. At this level, 153
the rules and procedures are limited and the person has to rely on intuition and creativity to cope 154
with the situation.
155
As stated earlier, a music ensemble’s resilience is based on the ability of its members to 156
provide proper responses to unexpected perturbations. If we combine the response providers 157
(individuals and team) with the cognitive levels (skill, rule, and knowledge), we get a 3×2 matrix 158
that can be adopted as the background for the resilience framework model (Figure 1). This 159
framework represents the information flow along the six steps resulting from the 3×2 matrix. The 160
red vertical arrows flanking the matrix represent the amount of perturbation (left arrow) and 161
cognitive effort framed as the SRK model (right arrow). The two parameters are correlated 162
because an increase in task perturbation leads to an increase in attentional engagement (Posner &
163
Rothbart, 2007). The clockwise cycle starts at the individual level when the musician is playing 164
at the skill-based level (bottom left part of the matrix). Here the musician is playing without any 165
particular cognitive effort; the situation appears to be routine and highly predictable. However, 166
when a perturbation pops up (internal or external to the team), the cognitive level moves from 167
skill to rule, at which point the performer is focused on execution and tries to control the 168
situation or change the repertoire of actions. If this coping is not effective, or the perturbation is 169
stronger than expected, the musician moves to the knowledge level and tries to find an effective 170
way to dampen the perturbation. This transition from skill to knowledge level is based on 171
situation awareness, that is, the capacity to notice and understand the current moment and foresee 172
the evolution of events. The player alone is not able to cope with the situation and therefore has 173
to communicate to the team (nonverbally, e.g., with eye and head movements, with arms and 174
posture) that the situation needs flexible adaptation. This communication process leads the whole 175
team to the knowledge level. Now, all players are under the burden of cognitive effort and share 176
a common understanding of the perturbation. They cannot play for long at this level and must 177
find a way to cope with the problem, implicitly finding a strategy to adapt and constrain the 178
perturbation. Now they have moved from the knowledge- to the rule-based level. If the solution 179
is effective, the team monitors the success of the adaptation and carries on playing, slowly 180
moving back to the skill-based level. Eventually, all team members return to the skill level and 181
the perturbation is under control. We claim that a resilient system can implement such a cycle, 182
passing through the four main processes grounded in NTS (the four blue arrows): (1) situation 183
awareness, (2) communication, (3) team adaptation, (4) individual adaptation.
184
185 186
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Figure 1 – The resilience framework (modified from Bracco, 2013) as applied to the three test cases considered in this chapter: (A) the string quartet, (B) the
orchestra. Visualization of behavior based on recorded motion capture data is also presented for each test case.
This entire cycle is performed with cognitive effort and can be facilitated by a leader, 188
when present (e.g., the orchestra director). The leader is particularly sensitive to perturbations 189
and can quickly move to the knowledge level and share this assessment with the team, helping 190
the team members to adapt and maintain a good performance. If the leader is absent (e.g., in a 191
AA
BB
CC
quartet), anyone can become a leader, or the leadership can be shared among the team. All 192
members can engage in the SRK process in parallel and can share the adaptation by means of 193
constant, multimodal, nonverbal feedback with each other (e.g., back-channeling; see Moran, 194
Hadley, Bader, & Keller, 2015). The following section presents two test cases selected from the 195
literature to provide evidence for this claim and to demonstrate how a music ensemble, and more 196
generally music practice, can be positively compared with a specific type of resilient system, one 197
that is highly exposed to risk.
198 199
Advantages of using the resilience framework to analyze music ensemble performance 200
Resilience can provide a useful conceptual framework for the investigation of the 201
dynamic adaptation that usually occurs within music ensembles. For instance, it allows detection 202
of the qualities of a leader and that leader’s impact on task achievement (e.g., information 203
sharing or knowledge synthesis). Similarly, this framework can help with the understanding of 204
the decision-making processes in an emotionally vivid environment and of the cognitive efforts 205
of all the actors involved in the management of perturbations. Such a conceptual framework can 206
thus be shared by professional musicians to address issues of performance (e.g., how to foster 207
individuals’ adaptation to stressful situations, how to increase the team’s flexibility and 208
adaptation to perturbations, and so on).
209
In order to concretely illustrate the application of the resilience model to music 210
ensembles and demonstrate its heuristic power, we selected illustrative examples from the most 211
recent literature on music ensemble performances that integrate quantitative measurements of 212
expressive behavior in individuals and groups. From such a perspective, the resilience approach 213
represents a way to integrate these original measurements within a broader frame, which is 214
useful for better interpreting the behavioral, emotional, and cognitive processes at play. This 215
approach may shed light on the way that musicians behave in order to perform the cooperative 216
and emotionally engaging task of playing in an ensemble, and it may also identify commonalities 217
and specificities of music contexts regarding other group activities.
218
The selected papers do not explicitly address resilience, but the variables and the 219
behaviors observed in these experiments correspond to the operationalization of resilience. Our 220
aim is to propose the resilience approach as a heuristic framework to revisit these processes and 221
find links between them that are not explicitly addressed with the current theories.
222
We claim that resilience processes are involved in the two cases that we present. They 223
could be quantitatively measured by observing that, besides perturbation, the group succeeds in 224
reaching a high level of performance measured in terms of the audience’s aesthetic evaluation 225
and through the self-reports of the musicians themselves. In addition, future research could 226
measure resilient performance by means of more quantitative measures such as those presented 227
in the papers (e.g., level of synchronization, driving forces; see, for example, Glowinski, 228
Dardard, Gnecco, Piana, & Camurri, 2014).
229
230
Test cases 231
1. Leadership (symphonic orchestra): being resilient within and in front of a large group 232
The first test case is related to the interaction between the orchestra members and the 233
conductor. The resilience framework can help in understanding the process by which the 234
conductor manages the continuous attentional shift of musicians to ensure a robust group 235
performance.
236
A study by Gnecco, Glowinski, Sanguineti, and Camurri (2014) aimed to investigate 237
whether the head movements of a group of players in an orchestra can be used to measure the 238
levels of visual attention toward the conductor and the music stand under various conditions 239
(Stiefelhagen & Zhu, 2002): (i) the type of conductor (three levels of conducting expertise 240
related to the conductor’s training, including local or international experience); (ii) the music 241
piece (belonging to the orchestra’s repertoire but with three musical styles: classic, romantic, and 242
contemporary); and (iii) the moment of the music piece (either at the beginning or at the end of 243
the piece, when synchronizing the musicians to start or end together is a key issue; or in the 244
middle of the piece, when the different sections of the orchestra, winds, and chords must be 245
conducted strategically to create a homogeneous sound).
246
The behavioral data relate specifically to dynamic expressive head movements. Head 247
movements represent a common focus of interest in the literature, as they are ancillary gestures 248
(Gnecco et al., 2014). They are not prescribed by the music score to the same extent as the 249
movement of the bows, for example, and can reveal communicational intent or emotional 250
expression in a more straightforward manner. A set of features derived from head movement 251
(direction, angular velocity, and variance over time) was sufficient to evaluate the dynamics of 252
attention between the musicians and the conductor over the entire performance and over its 253
several repetitions. One main finding was that the level of attention decreased considerably over 254
time: (a) from the beginning of the piece to its end, and (b) from the first repetition to the last.
255
For the former aspect (a), the authors pointed out that looking at the conductor at the beginning 256
of the piece was the only way for the musicians to synchronize themselves (no audio feedback 257
from the musicians in the orchestra was available in that moment). As for the latter aspect (the 258
decreasing level of attention over several repetitions of the same piece), it seemed that the 259
musicians quickly recorded the specific gestural style of the conductor in one piece, building up 260
complex relationships between musical moments and related conductor’s gestures. Afterward, 261
only a rapid glance was sufficient to understand the conductor’s follow-up indications. The 262
authors named such a process the “memory effect,” which can be rephrased as the concept of 263
procedural memory and the process of chunking sensory-action dynamics. This effect seems to 264
be moderated by the conductor. The authors did not provide any supplementary explanation 265
about this aspect, but one of the conductors, the one with the highest training level, received a 266
relatively higher level of attention from the musicians throughout the various rehearsals.
267
Moreover, the performances with this conductor were also those in which the musicians gave the 268
highest ratings for performance satisfaction.
269
Reinterpreting these results within a resilience framework can provide intriguing insights.
270
For instance, the dependence between the conductor and the musicians can be more 271
systematically explored and differences in leadership uncovered, even in those cases in which 272
there are no apparent perturbations, as was the case in this latter study. In fact, the SRK model 273
can fit all kinds of situations, not only those affected by perturbations. Moreover, the resilience 274
approach can explain the leadership role in managing musicians’ attention during the 275
performance. At the beginning, musicians are at a knowledge level because they lack 276
information about synchronization, and this is why they need to look at the conductor. However, 277
during the performance, they typically have to move to a skill level, as they do not need to 278
concentrate on the conductor until the end of the score. Here, the role of the conductor is crucial 279
because a capable conductor is able to help the team not perform at the skill level by constantly 280
triggering shifts to the knowledge level for dynamic adaptations. Thus, in the study by Gnecco et 281
al. (2014), the high ratings for performance satisfaction and level of attention observed with the 282
highest skilled conductor can be explained by the fact that the conductor stimulated the team to 283
dynamically move along the SRK cognitive ladder, possibly stressing expressive performance 284
beyond the mere skill-based execution of the score or building up a new dynamic representation 285
(e.g., through chunking processes and procedural memory) of the musical performance. This 286
makes the musicians shift to the knowledge level, which is cognitively demanding, but can also 287
lead to higher satisfaction because of the deployment of cognitive resources to creative, artistic 288
expressivity and to the enjoyment of the performance in the so-called flow state 289
(Csikszentmihalyi, 1990).
290 291
2. Self-team management (string quartet): being resilient within a small group of equal 292
partners 293
String quartets have been identified as a particularly promising context for investigating 294
social interactions. The resilience framework can give insight into the process by which 295
musicians can handle the continuous perturbation produced by the complex interplay observed 296
within the ensemble. The string quartet scenario involves a particular social structure. In a string 297
quartet, all the musicians contribute equally to the performance of the group. There is some 298
degree of leadership, usually played by the first violinist, but not the kind of hierarchy that can 299
be seen in an orchestra (conductor or concertmaster vs. other musicians). From this perspective, 300
the string quartet has been described as a self-managed team, that is, a working structure in 301
which all partners share roughly equal responsibility in the development of a common project 302
(Gilboa & Tal-Shmotkin, 2010).
303
A study by Glowinski, Dardard, Gnecco, Piana, and Camurri (2014) investigated 304
expressive nonverbal interaction in a string quartet, starting from the behavioral features 305
extracted at the individual and the group level. Four groups of features were defined, which were 306
also related to head movement and direction. They were used to gain insight into the expressivity 307
and cohesion of the performance, discriminating between different performance conditions. Such 308
features included, for example, the convergence of the direction of the heads toward a common 309
reference (e.g., the ear, a kind of imaginary listener that musicians imagine to coordinate with 310
one another; see Figure 1: the illustration of the arrows starting from the musicians’ heads 311
converging onto the conductor). The findings obtained from the analysis showed that using these 312
features alone or in combination may help in distinguishing between two types of performance:
313
(a) a concert-like condition, in which all musicians aimed at performing their best, and (b) a 314
perturbed condition, in which the first violinist devised alternative interpretations of the music 315
score without having previously discussed them with the other musicians.
316
Specifically, the authors found that the heads’ convergence toward a shared reference 317
(such as the ear) was positively correlated with a highly satisfying, engaging, and expressive 318
type of performance (as reported in post-performance questionnaires) (see Figure 1). Such a 319
convergence may allow for a higher variability of the head’s movement among all participants 320
during the performance (measured with their respective standard deviations), hence optimizing a 321
musician’s capacity to look for salient nonverbal information at key moments during the 322
performance (Badino, Ausilio, Glowinski, Camurri, & Fadiga, 2014). In contrast, in a much less 323
satisfying expressive performance such as the perturbed condition, the string quartet musicians’
324
head movements seemed to be more constrained, revealing much less variability and a higher 325
focus toward only one musician, here the first violinist. Interestingly, whereas self-reported 326
expressivity dramatically decreased in the perturbed condition in which the second violin, the 327
viola, and the cello had to guess and anticipate the first violin’s improvised and unusual 328
interpretation, the self-reported group coordination remained high. The results of this study 329
replicated previous studies on music ensemble performance (e.g., Davidson, 2012), but did so 330
with quantitative analysis. It has been suggested that musicians pay attention to other performers’
331
heads to better predict the performers’ upcoming actions (Badino et al., 2014). This attention is 332
particularly obvious when the behavior of another musician is difficult to predict, as it provides 333
information that can be transmitted to the other musicians mainly through movement and gaze 334
direction, constraining all the other musicians to tightly follow to maintain group cohesion.
335
However, this study emphasized that the high expertise of the musicians in the string quartet 336
could be decisive in attaining such cohesion despite a challenging performance situation.
337
These studies highlighted the potential of the string quartet scenario as a test case to study 338
group behavior in social, emotionally engaged, and creative activities that take place in 339
naturalistic settings. From this perspective, the resilience approach could lead to better 340
formalization of the issue. The advantage would be twofold: on the one hand, it will allow the 341
revisiting of group dynamics within this music ensemble and other music ensembles such as an 342
orchestra, as noted earlier. On the other hand, it may also be useful for reusing of the quantitative 343
behavioral features developed in the context of string quartets so that they can be applied to other 344
small groups of highly skilled people: not necessarily musicians, but dancers, athletes, or others 345
(e.g., firefighters).
346
In this case, we see that in the perturbed condition, the musicians moved their attention 347
toward the source of unexpected variety (the first violinist). They were playing at the skill level 348
when they noticed the perturbation, and so they moved up to the knowledge level, trying to cope 349
with the problem. They then implicitly coordinated themselves to move their attention toward the 350
first violinist and were able to move down from the knowledge to the rule and skill levels.
351
352
353
354
Conclusion 355
In this contribution, we provided a novel conceptual framework, based on the application of the 356
resilience concept, for the investigation of the strategies developed by ensemble musicians at 357
various levels of expertise to achieve coordination and a satisfying level of individual and group 358
expressivity. One of the main aims of this approach is to reveal the compromise achieved by 359
most experts between a risk-taking attitude and a robust capacity to cope with internal 360
perturbations (e.g., individual stress, emotions) and related external perturbations (e.g., audience 361
presence, noisy environment). We thus proposed examples, taken from published studies on 362
music performance, of critical situations in which the individual and group factors that influence 363
the success of the performance could be thoroughly studied through the resilience framework.
364
We maintain that this framework can provide an original and incisive perspective on 365
known cases typical of music ensembles, which can also have implications for the development 366
of novel strategies for training musicians. Given its common conceptual apparatus with other 367
organizational contexts, this resilience-based approach can also facilitate knowledge transfer 368
between musical and other contexts related, for example, to business or other social groups in 369
joint activities. From this perspective, this approach opens novel applications of music-inspired 370
situations in order to restructure, modify, and improve business situations.
371 372
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