Qualifications: PhD (Open); MA (Music) (Open); MA (Mathematics) (Cambridge); Fellow of the Institute of Actuaries
I graduated from Girton College, Cambridge, in 1986 with a first class honours degree in mathematics. I then qualified as an actuary and worked in a life assurance company for several years, before taking voluntary redundancy and deciding to pursue my long-term interest in music. I began studying music with the Open University, working through all of the undergraduate modules and then the MA. This led on to a PhD – ‘Statistics in Historical Musicology’ – completed in 2014 under the supervision of Professor David Rowland (music) and Professor Kevin McConway (statistics). The subject of my thesis brought together my skills in music research with my previous experience in actuarial mathematics and statistical modelling and analysis.
Recent publications include versions of my MA dissertation, and of the project completed whilst studying for the MA. I have presented on various aspects of my research at conferences organised by the Open University and by the Royal Musical Association. I am the author of two units (10 and 11) of the course materials for A873 (MA in Music Part 1), based on my doctoral thesis, and continue to provide support to this course in respect of statistical and quantitative methods. As an Honorary Associate with the Open University, I have supported Dr Robert Samuels with some quantitative analysis relating to his research on symphonies, and have recently presented conference papers on the migration patterns of Russian composers, and on British composers in the nineteenth-century German sheet-music market.
I am Company Secretary and Treasurer of a professional chamber orchestra, the Bristol Ensemble, and a regular volunteer at Dartington International Summer School. I also play the piano and compose music.
My main interest is in the application of quantitative methods in the study of music history. There are large quantities of data relevant to the study of music history, yet they have rarely been studied statistically to shed light on the large scale trends and patterns in the musical world. My interest extends from the methodological aspects, via the characteristics of the various datasets, to the application of these techniques to address real musicological questions. There are several loose ends from my doctoral research that I would like to pursue, including the analysis of a broader range of sources, the automation of data extraction from historical datasets, and the implications of a ‘big data’ approach to these historical sources.
I am strangely drawn to non-standard musicological questions that require innovative methodological approaches. These include investigating the large scale patterns within the population of musical works, the processes leading to fame or obscurity, and the behaviour of musical memeplexes.