Sociology, Philosophy, and Anthropology, University of Exeter, UK es431@exeter.ac.uk
Keywords: Performance, mobile music listening, interviews, shadowing
Background: Performance can be understood in many different ways. The immediate association is with something that happens on a stage, but there are other definitions of performance, too. Goffman (1956) sees performance as conveying an impression, as self-presentation. But performance is also performance to self and as such it can involve self-regulation and self-management. When taking into account the chronology of a performance, the preparation, actual performance and outcome of it, performance can be understood as having a history and can be analysed as a Musical Event (DeNora, 2003). Mobile music listening has been looked at from a
25th Anniversary Conference of the European Society for the Cognitive Sciences of Music, 31 July-4 August 2017, Ghent, Belgium 50 variety of perspectives, but performance has not often been one of them. Aims: This poster will demonstrate how all of these different interpretations of performance can be found in participant's own descriptions of their mobile music listening experiences. Music gives support in everyday life, thereby re-performing it. Method: In interviews 11 mobile music listeners were given the opportunity to explain their behaviours and choices. Later on they were shadowed (DeNora, 2000), i.e. observed while displaying this behaviour in their natural environment, to validate what they had said before and to check for anything that was not mentioned earlier. Immediately after the shadowing there was another interview to enable the participant to explain what happened during the shadowing. Results: A person wearing headphones automatically conveys an impression to other people that needs to be adjusted occasionally in order to achieve a required, socially acceptable effect, e.g., not shutting others out when in their presence. On the other hand it can also be used to avoid being overtly rude by indicating prior engagement. It will be shown through the example of one participant how the scheme of The Musical Event facilitates deeper understanding of the mobile music listener and his behaviour. He prepares his devices and the music on it meticulously, has reasons for listening to particular pieces of music, and knows exactly how to fulfill his needs through mobile music listening. This is so successful that it leads him to display this behaviour repeatedly. Performance as self-regulation has been the topic of studies before. Here it will be demonstrated that some participants are very aware of the emotional effects music has on them, and that others utilise music in specific ways during exercising. Conclusions: Mobile music listening can be used to re-perform everyday life in several different ways, using multiple definitions of the word “performance”. It is a complex behaviour that reveals new perspectives depending on the angle from which it is observed.
References
DeNora, T. (2000). Music in Everyday Life. Cambridge: Cambridge University Press.
DeNora, T. (2003). After Adorno. Rethinking Music Sociology. Cambridge: Cambridge University Press.
Goffman, E. (1956). The Presentation of Self in Everyday Life. Edinburgh: The University of Edinburgh Social Sciences Research.
Poster 9
Psychological predictors of engagement in music piracy Steven C. Brown
*1, Amanda E. Krause
#2*Strathclyde Institute of Pharmacy and Biomedical Sciences, The University of Strathclyde, Scotland, #Melbourne Conservatorium of Music, The University of Melbourne, Australia
1steven.c.brown@strath.ac.uk, 2amanda.krause@melbourne.edu.au
Keywords: Music piracy, music engagement, everyday listening, uses and gratifications
Background: Designed to appease the desire to listen to music freely and conveniently, music-streaming services such as Spotify are exceptionally popular nowadays. Yet, music piracy remains prevalent. Assuming a psychological perspective, the present study considers why people might choose to engage in music piracy (the practice of illegally sourcing music) when so many popular and varied legal services now exist. Aims: The present study considered the relationship between music piracy and broader musical engagement practices. In particular it addressed two research questions: (RQ1) beyond demographics, can psychological concepts (i.e., personality and identity) as well as music engagement (i.e., listening engagement and format use) explain piracy attitudes; and (RQ2) are the uses and gratifications associated with one’s preferred format related to piracy attitudes? Method: Three hundred and ninety six USA, UK, and Australian residents (38.60% USA, 26.50% UK, 34.80% Australia) completed an online questionnaire. Ages ranged from 16-71 years (M = 34.53, Mdn = 20, SD = 8.98); 71.00% of the sample was female, 28.00% was male, and 1.00% of participants identified as ‘custom’.
25th Anniversary Conference of the European Society for the Cognitive Sciences of Music, 31 July-4 August 2017, Ghent, Belgium 51 Participants completed Brown and MacDonald’s (2014) Attitudes Towards Music Piracy (AMP-12) scale, Langford’s (2003) short five-item personality questionnaire, Brown and Krause’s (2016) 49 Format Uses and Gratifications Item measure, and Krause and North’s (2016) music-technology identity measure. Additionally, participants indicated the format they used most often to listen to music (of six formats: physical (i.e., CD, vinyl, cassette), digital files (i.e., mp3), free digital streaming, paid-for digital streaming, radio, and live music); indicated how important they consider music in their lives; and estimated how many hours they listen to music daily.
Individuals also reported their age, gender, whether they held a University qualification, and their country of residence. Results: RQ1: The Generalized Linear Mixed Method analysis that considered whether psychological constructs and music engagement variables accounted for music piracy attitudes was statistically significant, F (15, 366) = 4.391, p < .001, np2 = .050. In particular, conscientiousness was negatively associated with the AMP score, such that that those individuals favouring music piracy were easy-going and disorderly. Post-hoc pairwise comparisons revealed that males demonstrated more favorable piracy attitudes than females (β = 0.234 [0.069, 0.399], t (366) = 2.785, p = .006, η2 = .021). Moreover, individuals using digital files and paid-for streaming services were significantly more likely to endorse positive piracy attitudes than those using physical formats; and users of free streaming services were significantly more likely to endorse more favorable piracy attitudes than users of physical formats, digital files, and the radio. RQ2: The generalized linear mixed method analysis that considered how the eight format uses and gratification dimensions related to piracy attitudes was statistically significant, F (8, 283) = 5.715, p < .001, np2 = .079. In particular, the value for money dimension was positively associated with more favorable piracy attitudes, while the connection uses and gratification dimension (characterized by emotionally connecting with music) was negatively associated with favorable piracy attitudes.
Conclusions: The associations between positive piracy attitudes and being male and expressing low levels of conscientiousness replicate findings reported elsewhere (Brown & MacDonald, 2014). The preference for accessing music digitally was also associated with engagement in music piracy, suggesting that even the seemingly-infinite catalogues of on-demand music are not enough to deter music piracy. Furthermore, with regard to uses and gratifications, results suggest that music piracy is driven by a perception that buying music is poor value for money, rather than a reluctance to pay altogether. From a policy perspective, future research could seek to establish what it is that drives perceptions of value for money in relation to music consumption practices.
References
Brown, S. C., & MacDonald, R. A. R. (2014). Predictive factors of music piracy: An exploration of personality using the HEXACO PI-R. Musicae Scientiae, 18(1), 53-64.
Brown, S. C., & Krause, A. E. (2016). A psychological approach to understanding the varied functions that different music formats serve. In Proceedings of the 14th International Conference on Music Perception and Cognition (pp.
849-851). San Francisco, CA.
Krause, A. E., & North, A. C. (2016). Music listening in everyday life: Devices, selection methods, and digital technology. Psychology of Music, 44(1), 129-147.
Langford, P. H. (2003). A one-minute measure of the Big Five? Evaluating and abridging Shafer’s (1999a) Big Five markers. Personality and Individual Differences, 35, 1127–1140.
Poster 10
»I don’t like that!« Disliked music and its rationales Taren Ackermann
Music Department, Max Planck Institute for Empirical Aestheticy, Germany taren.ackermann@ae.mpg.de
Keywords: Musical taste, disliked music, self-concept
25th Anniversary Conference of the European Society for the Cognitive Sciences of Music, 31 July-4 August 2017, Ghent, Belgium 52 Background: In Western cultures, musical taste – i.e. a particular attitude towards music (Farnsworth, 1969) – is an important aspect of one’s self-concept. As an affective and expressive medium, music not only serves to satisfy emotional and social needs, rather, it can be used to create and affirm one’s own identity. Until now, research mainly focuses on explaining and understanding preferred music and its respective functions. Only few studies investigate the reasons and functions of disliking music. Aims: Therefore, the aims of this study were to explore the breadth of people’s disliked music as well as their rationales for disliking specific music. Method: Qualitative semi-structured interviews were conducted (stratified sample with five age groups, N = 21 with 52 % female). In preparation to the interview participants were asked to bring a list of their disliked music with them. Based on this list, they were asked for the reasons why they disliked each item on the list, what aspects exactly they disliked and what they would do when exposed to their disliked music. All interviews were fully transcribed and analyzed using structured content analysis. Results: Various musical as well as nonmusical aspects were identified as being important in order to explain participant’s reported disliking, e.g., rhythm, lyrics, artists / performers, fans or performance settings. Reasons for musical dislikes were divided into three categories:
personal, social and material reasons. Participants reported using musical dislikes explicitly to express their identity and to establish and reinforce a negative self-image, which they perceived and presented as highly incongruent with their self. The social category of reasons contained all rationales associated with peer groups or family, either by means of social affiliation or distinction. Material reasons comprised of rationales based on musical knowledge and music-related quality standards of the participants. In addition, participants discriminated between several intensities of musical dislikes ranging from mild dislikes to very strong rejections of specific pieces, artists or entire musical styles. They also reported that their dislikes were stable over long periods of time and rarely changed. Conclusions: The study provides further insights into the extent of people’s musical dislikes and the rationales behind those dislikes. Results from this study are in line with Behne’s model for the rationales of musical taste (Behne, 1986) and the psychological theory about possible selves (McCall, 2003). Participants reported using their disliked music to create, affirm and present their self. While they were able to talk about how their musical dislikes were associated to their self, they could not say in which way their preferred music related to their self-concept. This indicates that disliked music might be an easier way for the participants to verbalize and present their self-concept compared to speaking about their preferred music (see also Berli, 2014). Therefore, future research should take into account both – likes and dislikes – when investigating musical taste.
References
Behne, K. E. (1986). Hörertypologien: Zur Psychologie des jugendlichen Musikgeschmacks. Perspektiven zur Musikpädagogik und Musikwissenschaft: Vol. 10. Regensburg: Gustav Bosse Verlag.
Berli, O. (2014). Grenzenlos guter Geschmack: Die feinen Unterschiede des Musikhörens. Kultur und soziale Praxis. Bielefeld: Transcript.
Farnsworth, P. R. (1969). The Social Psychology of Music (2. ed.). Ames: Iowa State University Press.
McCall, G. J. (2003). The me and the not-me. Positive and negative poles of identity. In P. J. Burke, T. J. Owens, R. T.
Serpe, & P. A. Thoits (Eds.), Advances in Identity Theory and Research (pp. 11-25). New York: Kluwer Academic/Plenum Publishers.
Poster 11
The influence of meter on harmonic syntactic processing in music. An ERP study Rie Asano
*1, Clemens Maidhof
*#2*Department of Systematic Musicology, University of Cologne, Germany, #Department of Music and Performing Arts, Anglia Ruskin University, Cambridge, United Kingdom
1rie.asano@uni-koeln.de, 2clemens.maidhof@anglia.ac.uk
25th Anniversary Conference of the European Society for the Cognitive Sciences of Music, 31 July-4 August 2017, Ghent, Belgium 53 Keywords: Syntax, structure building, rhythm, harmony, EEG, ERAN
Background: Musical syntax includes tonal-harmonic structures, but also rhythm. Although several theoretical investigations stressed the importance of the interplay between tonal-harmonic and rhythmic (and specifically metrical) aspects for musical syntax, neuroscientific evidence is lacking. Aims: Thus, the aim of the current experiment is to investigate the influence of meter on harmonic syntactic processing in music using event-related potentials, in particular the early right anterior negativity (ERAN). Method: Twenty-one participants (musicology students; 8 females; mean age: 23.3 years, range: 18-37 years) listened to musical sequences consisting of five chords of equal loudness, the final chord function being either tonally regular or irregular. The metrical importance of chords was manipulated by presenting the sequences in two blocks: each chord sequence was preceded by a one-bar percussion sequence either in a 4/4 or in a 3/4 meter. Thus, the final chord occurred either on a metrically strong (first) or weak (second) beat. To further induce a specific meter, participants had to detect rarely occurring chords with deviant timbre (p = .1) and judge as fast as possible whether they were on a strong or weak beat (e.g., by pressing the left button if the deviant was ‘on 1’ and the right button if it was ‘not on 1’). To accomplish the task, participants had thus to keep the induced metrical structure over a whole chord sequence.
The electroencephalogram was recorded with 24 scalp electrodes with a sampling rate of 500 Hz (SMARTING system). Data were offline rereferenced (linked mastoids) and filtered (0.25-25 Hz, FIR). Eye artefacts were corrected by performing an Independent Component Analysis and removing independent components contaminated with eye artefacts (EEGLAB). Other artefacts were automatically rejected. Event-related potentials (ERPs) for regular and irregular chords were averaged (-200 – 1000 msec) and statistically evaluated by repeated measures ANOVA. Moreover, behavioral data (d’ and reaction time) were analyzed. We hypothesize that if the metrical structure influences tonal syntactic processing, the ERAN shows larger amplitudes when chord sequences are presented in a 4/4 meter than in a 3/4 meter: in the former case, an irregular final chord is on the metrically strong beat and is considered to cause a much stronger syntactic expectancy violation, compared to when an irregular final chord is on a metrically weak beat. Results: The analysis of d’ values showed that participants detected the timbre deviants and judged their metrical positions above chance level (d’ (SD) = 4.66 (0.87) for 4/4 meter and d’ (SD) = 4.15 (0.98) for 3/4 meter). However, participants detected deviants faster in 4/4 than in 3/4 meter (t(20) = -3.9, p < .001). Compared to tonally regular chord sequence endings, tonally irregular endings elicited an ERAN which was maximal at around 200 msec in both 4/4 and 3/4 meter. An ANOVA with factor chord type (regular, irregular) and meter (4/4, 3/4) showed a main effect of chord type only (F(1, 20) = 69.4, p < .001), but no interaction between chord type and meter (F < 1). Conclusions: In the current study, the amplitude of the ERAN was not modulated by metrical importance. However, there are several aspects that need further consideration. For example, the meter induced by the timbre detection task was possibly not strong enough to influence ERAN. An analysis of the Beta band activity might help us to investigate whether different meters were induced in participants, as has previously been shown. Moreover, the current experimental stimuli did not include metrical expectancy violations, and the ERAN might be influenced only by simultaneous syntactic expectancy violations. It is also possible that meter processing may influence cognitive processes reflected in later ERP components (e.g., N5). Alternatively, metrical structure building might be a lower-level process and differ fundamentally from harmonic structure building.