2018
DOI: 10.1177/1077800418806618
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Complexity in Global Musical Belongings: Post-human Methodology in Analysis of Marginalized Teenagers in Oslo

Abstract: Analyzing global complexity demands for a sensitive perspective on power and hierarchies. This article is an inquiry on how post-human theories can contribute to analytical methodological tools with the aim of emphasizing nuances, differences and marginalized local, national and global strings of musical affiliation.

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Cited by 2 publications
(1 citation statement)
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“…There is now a common understanding that qualitative methods including case study, phenomenology, grounded theory, narrative inquiry, or action research, among others stand alongside or along with quantitative-randomized control trials, other experimental designs, large-scale surveys or measurement or big data studies have been used to examine aspects of music listening, performance, or creation. Other longstanding methodologies such as historical, philosophical, and comparative approaches along with various literature review methodologies help us answer our research questions and more recently neuroimaging studies, machine learning and VR have been used to address our research questions (e.g., Bowman & Frega, 2012;Elliott et al, 2019;González-Moreno, 2012;Hovde, 2019;McPherson & Welch, 2012;Orman et al, 2017;Pando-Naude et al, 2021).…”
Section: Developing Research Designmentioning
confidence: 99%
“…There is now a common understanding that qualitative methods including case study, phenomenology, grounded theory, narrative inquiry, or action research, among others stand alongside or along with quantitative-randomized control trials, other experimental designs, large-scale surveys or measurement or big data studies have been used to examine aspects of music listening, performance, or creation. Other longstanding methodologies such as historical, philosophical, and comparative approaches along with various literature review methodologies help us answer our research questions and more recently neuroimaging studies, machine learning and VR have been used to address our research questions (e.g., Bowman & Frega, 2012;Elliott et al, 2019;González-Moreno, 2012;Hovde, 2019;McPherson & Welch, 2012;Orman et al, 2017;Pando-Naude et al, 2021).…”
Section: Developing Research Designmentioning
confidence: 99%