The course introduces the latest methodological developments related to causal inference in the social sciences. The course begins with the basics of the formal theory of causal reasoning (by Judea Pearl) and its philosophical foundations. We will then explore more specific issues and methodologies, such as the concept of social mechanism, how to construct a good causal variable, quasi-experimental designs, field and laboratory experiments in the social sciences, and case-based process tracing. The course format is a reading seminar with recent methodological research articles as course material. In addition, each student will make a short presentation on an empirical research article related to the methodological topic in question. Default example articles are provided by the teacher, but students can also make suggestions based on their interests (such as their thesis topic).

Course outline:

1. Introduction
2. Foundations of Causal Inference I
3. Foundations of Causal Inference II
4. Foundations of Causal Inference III
5. Causal Mechanisms and social theory
6. Mechanistic thinking and statistics
7. What is a good causal variable?
8. Quasi-experimental strategies
9. Qualitative evidence and process tracing I: within-case
10. Qualitative evidence and process tracing II: comparative process tracing
11. Experimental social science: field experiments
12. Experimental social science: laboratory experiments
13. Summing up
14. Exam

Target audience: masters and PhD students in the social sciences and philosophy students interested in philosophy of science. Maximum number of participants: 12.

The purpose of this course is to provide a review of the currently discussed topics in the philosophy of the social sciences. The lectures are given by researchers in the field. The course is methodologically oriented and the lectures combine exposition of philosophical argumentation with ample use of concrete case studies. 

Course outline:

1. 12.1.  Introduction (to the field): Jaakko Kuorikoski
2. 19.1.Explanation and understanding revisited: Jaakko Kuorikoski
3. 26.1. The micro-macro issue: Petri Ylikoski
4. 2.2. Process tracing and causal mechanisms: Tuukka Kaidesoja or Jaakko
5. 9.2. Growing virtual societies and big data: Samuli Pöyhönen
6. 16.2. Experimental social science: Michiru Nagatsu
7. 9.3. Social science and values: Kristina Rolin
8. 16.3. Social science and objectivity: Inkeri Koskinen
9. 23.3. Social norms: Joonas Ottman and/or Jaakko Kuorikoski
10. 6.4. Social ontology: Raul Hakli and/or Pekka Mäkelä
11. 13.4. Human nature and the biosciences: Tomi Kokkonen & Jaakko Kuorikoski
12. 20.4. Social science and policy: Caterina Marchionni

Level:

PhD-students and advanced students of social sciences

Participants write short (2-3 page) essays on five topics which they see as most relevant for their studies. The writing assignments are also based on the provided background material.

The course introduces the latest methodological developments related to causal inference in the social sciences. The course begins with the basics of the formal theory of causal reasoning (by Judea Pearl) and its philosophical foundations. We will then explore more specific issues and methodologies, such as the concept of social mechanism, how to construct a good causal variable, quasi-experimental designs, field and laboratory experiments in the social sciences, and case-based process tracing. The course format is a reading seminar with recent methodological research articles as course material. In addition, each student will make a short presentation on an empirical research article related to the methodological topic in question. Default example articles are provided by the teacher, but students can also make suggestions based on their interests (such as their thesis topic).

Course outline:

1. Introduction
2. Foundations of Causal Inference I
3. Foundations of Causal Inference II
4. Foundations of Causal Inference III
5. Causal Mechanisms and social theory
6. Mechanistic thinking and statistics
7. What is a good causal variable?
8. Quasi-experimental strategies
9. Qualitative evidence and process tracing I: within-case
10. Qualitative evidence and process tracing II: comparative process tracing
11. Experimental social science: field experiments
12. Experimental social science: laboratory experiments
13. Summing up
14. Exam

Target audience: masters and PhD students in the social sciences and philosophy students interested in philosophy of science. Maximum number of participants: 12.

The purpose of this course is to provide a review of the currently discussed topics in the philosophy of the social sciences. The lectures are given by researchers in the field. The course is methodologically oriented and the lectures combine exposition of philosophical argumentation with ample use of concrete case studies. 

Course outline:

1. 12.1.  Introduction (to the field): Jaakko Kuorikoski
2. 19.1.Explanation and understanding revisited: Jaakko Kuorikoski
3. 26.1. The micro-macro issue: Petri Ylikoski
4. 2.2. Process tracing and causal mechanisms: Tuukka Kaidesoja or Jaakko
5. 9.2. Growing virtual societies and big data: Samuli Pöyhönen
6. 16.2. Experimental social science: Michiru Nagatsu
7. 9.3. Social science and values: Kristina Rolin
8. 16.3. Social science and objectivity: Inkeri Koskinen
9. 23.3. Social norms: Joonas Ottman and/or Jaakko Kuorikoski
10. 6.4. Social ontology: Raul Hakli and/or Pekka Mäkelä
11. 13.4. Human nature and the biosciences: Tomi Kokkonen & Jaakko Kuorikoski
12. 20.4. Social science and policy: Caterina Marchionni

Level:

PhD-students and advanced students of social sciences

Participants write short (2-3 page) essays on five topics which they see as most relevant for their studies. The writing assignments are also based on the provided background material.

See the program at

http://www.uta.fi/yky/en/hegelcongress2018/home/program.html

Students are requested to be prepared to volunteer to help the conference organizers (many of whom are not local) with practicalities (where to find a janitor etc).

arto.laitinen@uta.fi