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Albrecht Schneider

Research Concepts in Systematic Musicology (18/03/10)

When founded as an academic discipline in the 19th century, musicology was regarded to comprise three major areas (or sub-disciplines): historic musicology, systematic musicology, and comparative musicology. While the tasks and methods assigned to the historic branch were relatively clear from the beginning, this could not be said of the systematic or of the comparative approach (since they were transdisciplinary in regard to theory and methodology, and were dealing with fundamental research being of relevance to musical acoustics and psychoacoustics, music perception and cognition). In the talk first a brief explanation of concepts of a system and of systematization will be given in order to elucidate the meaning of "systematic". Some fundamentals of Helmholtz's theory of sensation and perception shall be examined, followed by the cognitive approach chosen by Carl Stumpf (for his "Tonpsychologie" and other writings). In addition, some aspects of both approaches combined will be indicated. In the course of the 20th century, Gestalt psychology became very influential for music psychology. It has been given new impetus during the past decades (as part of the so-called 'cognitive turn'). New methodological and experimental paradigms that were set up in the 20th century included statistical models (e.g., Thurstone, Fisher, Pearson-Neyman, Cronbach). In behavioural sciences, a quantitative approach based on samples of subjects, empirical data collection, and statistics has since prevailed. Because statistical inference is perhaps the most common methodology also in areas like psychoacoustics and music psychology, a few remarks on the theoretical background of at least some of the models seem appropriate. The next era of research, starting in the 1960s and 1970s saw the use of the computer in various areas of acoustics, hearing research and psychophysics/psychoacoustics, and also in studies on music perception and cognition (making use of, for instance, neural networks). Some examples from previous and recent research projects at Hamburg will be provided in order to illustrate the methodologies discussed above.