![]() Quantitative objectivity is in a way a form of standardization, the use of rules to confine and tame the personal and subjective. ![]() There I emphasize that effective quantification is never a matter simply of discovery, but always also of administration, hence of social and technological power. This interest in the relations of the natural and the social is also central to my Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (1995). My first book, The Rise of Statistical Thinking (1986), was about the development of statistical ambitions and methods in fields ranging from the social science of statistics to biological evolution and thermodynamics. When I was a graduate student, it was just beginning. Historical and social research on data and statistics has become by now a flourishing international enterprise. Asylum numbers, in my view, were a notable early form of big data. Although an obsession with hereditary factors or genes appeared quite early, the work depended mainly on records of bodily measures and diagnosed health conditions, that is, on phenotypic more than genotypic data. After 1900, when Mendelism and biometry appeared on the scene, bringing bold ambitions for a new hereditary science, they quickly discovered that asylums and special schools were invaluable, not only for their data, but even for their research methods. Doctors and statisticians developed increasingly ambitious tabular technologies to draw out the implications of their data. Although patients formed the core population for hereditary study, some asylum doctors were working to extend their data empire to near and distant family members as early as 1840. Its basis was patient data, gathered up and printed in annual asylum reports. As a medical-social field it was framed by bureaucratic demands, yet it extended beyond them right from the start. My most recent book, Genetics in the Madhouse: The Unknown History of Human Heredity (2018), recovers a long-forgotten form of hereditary investigation that took shape in the 1820s. ![]() Most of my work has involved in some way the uses of statistics, calculation, numbers, measures, and data. I teach various topics involving history of science, especially the human sciences.Īlready by 1980, I was interested in diverse sites of knowledge-making-not just universities and academics, but mining boards, statistical agencies (notably census offices), engineering corps, and mental hospitals. ![]()
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