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Lehrende: Prof. Dr. Elisabeth Allgöwer; Prof. Dr. Kai-Uwe Schnapp
Veranstaltungsart:
Seminar
Anzeige im Stundenplan:
Semesterwochenstunden:
2
Unterrichtssprache:
Englisch
Min. | Max. Teilnehmerzahl:
- | 18
Kommentare/ Inhalte:
The collection and processing of data on many facets of life is an important aspect of modern government and public administration and can be traced back to at least the 17th century. At about the same time private companies such as insurers and banks developed business models based on the systematic analysis of numerical information. Furthermore, the sciences, natural and social, strove to describe and understand the world through numbers. Big data seems to add a new dimension to these ongoing processes.
In this seminar, we discuss the interaction between numerical information, statistical theory and (substantive) theoretical explanation. We will start by looking at the beginnings of data collection by nation states and their administrations. In the course of the 19th century, statistical concepts changed the understanding of this information by providing tools for systematic analysis. Beyond being technical devices, concepts like average, median, representativeness of samples, normal distribution etc. convey meaning and unfold normativity. In which sense statistical theory is performative, is an aspect we will also discuss in these sessions. Furthermore, (substantive) theory interacts with the conceptualization of data, with data collection and with statistical analysis. National accounting is a case in point in view of the influence economic theory had on data construction on the one hand, the feedback on (macro-) economics once data and econometric tools were available on the other. Other examples we will draw on come from social statistics, such as occupational classifications. On this background, we will discuss the interaction between empirical and theoretical analysis in the social sciences more generally in this part of the seminar.
Lernziel:
(Based on the module handbook:) Students acquire the ability to apply, synthesize, and contrast methods and findings from the disciplines of political science and economics with respect to the specific issues raised in the seminar within the context of individual and collective decision-making.
Vorgehen:
From October to December seminar sessions will be devoted to discussing designated readings. In the first session, the program will be presented and presentations assigned. All students come prepared to the following sessions: they contribute to the debate on the basis of their prior reading of the designated texts. The sessions will start with a short input by assigned students: based on additional reading, they will explain the context of the readings and shed light on the key issues raised. By December all students have developed preliminary ideas for their paper projects and discussed them with one of the lecturers. During the block seminar in January students will present their work. Papers are due on March 15, 2020.
Literatur:
A list with the readings for all sessions will be available by the beginning of the semester. Background reading:
Desrosières, Alain (1998 [1993]) The politics of large numbers. A history of statistical reasoning. Translated from the French by Camille Naish. Harvard University Press. (Also available in German (e-book through UHH library): Desrosières, Alain (2005 [1993]) Die Politik der großen Zahlen. Eine Geschichte der statistischen Denkweise. Aus dem Französischen von Manfred Stern. Heidelberg: Springer.)
Hacking, Ian (1990) The taming of chance. Cambridge University Press.
Klein, Judy L. (1997) Statistical visions in time. A history of time series analysis, 1662-1938. Cambridge University Press.
Morgan, Mary S. (1990) The history of econometric ideas. Cambridge: University Press.
Tooze, J. Adam (2001) Statistics and the German State, 1900-1945. The making of modern economic knowledge. Cambridge University Press.
Zusätzliche Hinweise zu Prüfungen:
The grade will be based on the presentation in class and the seminar paper.
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