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OBME 2120 - Manufacturing Knowledge. Research Methods for Social Sciences

Type d'enseignement : Seminar

Semester : Spring 2018-2019

Number of hours : 24

Language of tuition : English



Course Description

The course teaches methods to understand the production of knowledge by social actors and to learn how to craft our own categories and interpretations of the actors' knowledge. It teaches how to study ideas and theories but it also teaches how to use social sciences concepts AND tools to understand ideas and theories. Rooted in the tradition of social sciences, science and technology studies and digital humanities, the course will provide the students with theories, methods and open access tools needed to analyze knowledge of social actors and conduct their own social sciences research. The starting point and philosophy of this methods course is the need to be as critical and questioning of our categories (as researchers) as we are of the categories and theories the actors we study deploy. This has consequences as trivial as the choice of the methods we use, the tools we use to build a corpus and the visualisations we adopt to illustrate our findings. By opening a dialogue with sources taken as a research object, the goal is not to produce a plain bibliography, but to build a quality research corpus, analyzed through both up-to-date qualitative and quantitative methods. This course trains reflexive social scientists, that is scholars who learn methods AND their limitations.

This year, the class demonstrations will use 2 case studies to present and test methods and tools. The case is Russia as an object of theories by French and American scholars and intellectuals. This is both a timely case to the extent that Russia is present in the media and that it is a polarizing object of study. It is also a case that offers a trove of methodological puzzles which will be as many possible projects for students. How do we talk about Russia and who sets the agenda of the conversation about soviet and post soviet Russia? By exploring a series of data sets of knowledge produced about Russia, we will use the same object (Russia from the prisms of USA and/or France) to explore data science applied to knowledge production in the context of international relations. We will look at a variety of materials and documents (university theses, scientific articles, think tank reports, books, popular articles) to understand how to organize a research project fraught with ideological pitfalls and easy sloppy interpretations.

Additional requested information:
This course is particularly well-suited for students who are interested in working on IR and transnational knowledge production. You do not have to be either a supporter or a critic of Russia-as-we-know-it and the course is not geared to make you a specialist of Russia. Indeed, the take away of these 12 weeks is methodological, not thematic. This is a project-based course and it follows a workshop approach. We meet every week and each student is expected to have a pro-active understanding of how a collective project works. Every weekly assignment and task is not only needed for the experience to be full and enriching. It is also a requirement for the synergy between class members to work. So this course is not good for a passive, free-riding option towards collecting a grade.


LEPINAY, Vincent-Antonin (Associate Professor, Sociology Department, Sciences Po)

Pedagogical format

A mix of lectures (short and limited to the beginning of the term, mostly during the first few meetings), readings and in class collective discussions, presentations of work-in-progress. The orientation of the course is that of a lab: we know the general direction that animates us but we invent collectively how we can collect, analyze and interpret data pertaining to the discourses about Russia. Come with an interest for experiments and discussions, and some suspicion for ready-made solutions.

Course validation

Students will have to do weekly mini exercises and they will also read a half dozen articles that will structure the philosophy of the course. The mini exercises will be either individual or collective's. They will be presented on a weekly or every other week basis. Overall, these presentations will count towards 40% of the final grade. Students will also write a final paper - and it will exploit all the works done during the weekly exercises. They will also count towards 40% of the final grade. Both the weekly exercises and the final papers can be individual or collective. It is usually better to keep groups to a size of 2 -3 students but in some cases it will be possible to assemble larger groups if a project requires many actions and a division of labor. For group projects, each group member will also evaluate the other students in her/his group using a zero sum metric. Peer evaluations will weigh 20% of the final grade. Students who will never work in groups will be evaluated solely on the basis of their weekly participations/contributions (50%) and final paper (50%).


It is a course designed to teach methods and skills. Exercises and hands-on tasks are not an option. They will be taught in class but they should be practiced as homework. Additional requested information: (eg ≤ to 3 hours, 3 to 6 hours or > to 6 hours): Expect between 3 and 6 hours weekly.

Required reading

  • Daston, L.J., Galison, P., 2010. Objectivity. Zone Books, New York. Introduction
  • Bowker, G.C., Star, S.L., 2000. “The Case of Race Classification and Reclassification under Apartheid”, in: Sorting Things Out - Classification & Its Consequences. MIT Press, Cambridge, pp. 195–225.
  • Desrosières, A., 2002. The Politics of Large Numbers - A History of Statistical Reasoning. Harvard University Press, Cambridge.

Additional required reading

  • Malia, M. 1999. Russia under Western eyes : from the bronze horseman to the Lenin mausoleum. The Belknap Press of Harvard University Press, Cambridge.