Theoretical Paradigms of the Political Sciences 1600-SZD-N-PTNP-PA
It is quite common to argue that conscious, active, and systematic use of theories in empirical research is a sign of scientific maturity and advancement. Yet, PhD dissertations fulfil this expectation to a limited extent only. For this reason, it is essential to pay close attention to the important role that a theoretical framework plays in the entire construction of a doctoral thesis and to the key contemporary research paradigms, debates, dilemmas, and choices that social science researchers face. At the same time, following the pluralist spirit, one should familiarise himself with those approaches that do not place theories at the centre. In general, this course will offer a road map that students will independently follow upon completion of the course to solve their own research dilemmas. For this reason, only a selected range of issues will be addressed. In all cases, the analysis of the foundations and rules of paradigms will be illustrated by looking at the way in which they have been used in the academic literature.
Course coordinators
Type of course
Prerequisites (description)
Learning outcomes
Knowledge (W; in Polish: “wiedza”) (the graduate knows and understands)
WG_01 to the extent enabling the revision of existing paradigms - the world’s achievements relating to theoretical
foundations as well as general and selected specific issues - relevant to a particular discipline within the social
sciences
WK_01 fundamental dilemmas of modern civilisation from the perspective of the social sciences
Skills (U; in Polish: “umiejętności”) (the graduate is able to)
UK_01 communicate on specialist subjects to a degree that enables active participation
in the international scientific research in the field of the social sciences
Social competences (K; in Polish” “kompetencje społeczne”) (the graduate is ready to)
KK_01 critically evaluate achievements within a given scientific discipline in the field of the social sciences
Assessment criteria
The written examination is the main method of assessment. Additionally, the systematic submission of weekly or biweekly homework assignments throughout the term is required to pass the course. End-of-term bulk submissions will not be accepted.
Today, Artificial Intelligence (AI) is easily accessible, and its potential is steadily growing. However, at this stage of doctoral training, broad AI use can be counterproductive, hindering the development of the doctoral student’s own voice and even creativity. For this reason, in this course AI must not be used for any short, written assignments, except for literature mapping under AIAS Level 2, understood only as research assistance (discovering topics, areas of interest, or potential sources). Assignments must not contain any content directly generated by AI. Doctoral students must independently read and critically assess every source they cite. AI tools may not summarise, paraphrase, or rewrite any part of the assignment text or the cited literature. No AI- or machine-translated text may appear in the assignments, including translations of the candidate’s own writing and of source quotations. Basic, non-AI spell- and grammar-checking functions of the text editor are not only permitted but recommended.
Bibliography
Bevir, Mark, and Jason Blakely. Interpretive Social Science: An Anti-Naturalist Approach. Oxford: Oxford University Press, 2018.
Blaikie, Norman W. H. Approaches to Social Enquiry. Cambridge: Polity, 2007.
Della Porta, Donatella, and Michael Keating. Approaches and Methodologies in the Social Sciences: A Pluralist Perspective. Cambridge: Cambridge University Press, 2008.
Godfrey-Smith, Peter. Theory and Reality: An Introduction to the Philosophy of Science. Chicago: University of Chicago Press, 2009.
Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago: University of Chicago Press, various editions.