The module serves three principal purposes. The first is to ground students in the language of social science research: research questions, independent and dependent variables, hypotheses, causality, etc. Students will come across these terms relentlessly in this module, in other modules, and throughout social science. It is thus important that you are able to use them readily and correctly. The second purpose is to familiarise yourself with the types of data and the practice of data analysis in the social sciences. Students are introduced to a range of sources from which they can access quantitative data. Student will also be introduced to the programming language R, which is widely used by academics and practitioners for the analysis of quantitative data. I will assume that students have no prior experience with any of this software, and so students will be given a full introduction to their use. The third purpose is to introduce a series of statistical techniques for the analysis of quantitative data. Some of the techniques are fairly simple, while others (especially those covered in the final weeks of the module) are advanced. The good news is that as the work becomes more challenging, the relevance of the techniques to modern social science research becomes more apparent.
- Module Supervisor: Ryan Bakker
- Module Supervisor: Howard Liu
- Module Supervisor: Kristian Gleditsch
This module presents quantitative methods essential to test hypotheses. The first part of the course concentrates on hypothesis testing, hypothesis testing using least squares, and some classic violations of the Gauss-Markov conditions. In this first part, we will cover cross-sectional and longitudinal models for continuous dependent variables.
The second part of the module focuses on more advanced models ubiquitous in political science based on maximum likelihood estimation and other estimation techniques, starting with the generalised linear model and its various outcome distributions and ending with advanced topics like inferential network analysis and causal inference.
The models and methods are approached substantively, mathematically, and computationally. We will replicate important results using computer programs. The module makes extensive use of the statistical programming environment R. In addition to the methods and software, we will cover some empirical applications to substantive questions. This is particularly important because students should familiarise themselves with the interpretation and presentation of empirical evidence.
- Module Supervisor: Philip Leifeld
- Module Supervisor: Zorzeta Bakaki
- Module Supervisor: Han Dorussen
The course is broken into a number of themes. In these weeks, we will examine how domestic and international politics drive trade, investment, financial, and immigration policies and outcomes. We will also look at the relationship between political institutions and economic outcomes as well as the effects of economic phenomenon on institutions. The class emphasizes the theoretical core and some current debates in the field but also aims to expose students to some nuts and bolts of topics related to political economy (broadly defined) and chief methods by which scholars acquire knowledge of the subject.
- Module Supervisor: Nicole Baerg
More specifically, it has three principal aims-
1. It introduces a range of ideas and concepts in analytical political theory and in ideology and discourse analysis.
2. It engages students in a series of close textual readings of selected essays, books and articles, with the aim of elucidating key concepts and ideas.
3. It examines a number of central debates in contemporary political theory.
Each of these aims is pursued in specifically designed seminars, and each seminar is organised around a number of objectives designed to achieve these aims. The objectives and questions are listed in the section detailing the overall programme and readings for the course. On completing this research seminar, a student ought to have a good understanding of a number of contemporary forms of political theorising and argumentation; and be fully aware of a number of central concerns and discussions in contemporary political theory. Finally, students should be in a position to develop and execute a Masters Research Dissertation in political theory.
- Module Supervisor: Mollie Gerver
It is traditional to divide the study of political theory into normative and empirical domains. Normative political theorists endeavour to construct, evaluate, justify and criticize the principles and norms underlying political practices, whereas positive political theorists are concerned to explain, understand and interpret political practices and events by constructing and testing abstract models of those practices. In recent years, this clear division has become somewhat blurred, as normative political theorists seek to ground their research in the description of empirical phenomena, or at least to speak to matters of empirical import, while positive political theorists have become more attentive to the implicit or explicit values that structure their research. The task of this module is to sensitize students to the presuppositions underpinning different approaches to questions of description, explanation, and critique.
- Module Supervisor: David Axelsen
- Module Supervisor: Shreyaa Bhatt
- Module Supervisor: Laura Montanaro
Class will meet once a week for 2 hours (120 min) during the Autumn and the Spring terms.
- Module Supervisor: Nicole Baerg
This module prepares students to replicate and expand published research. Replication consists on reproducing the empirical test presented in a study, with the data and modeling choices the author(s) used. It also involves analyzing the data accuracy and appropriateness of the modeling choices. For this module, expanding extant empirical research means that, after replicating the study, students should introduce a theory-informed modification that would allow them to build upon that study. This exercise intends to deepen the students’ understanding and critical evaluation of research strategies, to highlight the importance of transparency on our own research, and to foster the idea that scientific knowledge is a social enterprise.
GV914 is a prerequisite for taking this module.
INSTANT DEADLINE CHECKER –
Assignment Title |
Due Date |
Coursework Weighting* |
Feedback Due |
Replication proposal (memo) |
Week 31. |
10% |
Week 32 |
Replication proposal (class presentation) |
Week 31 |
10% |
The day of the presentation |
Replication report (memo) |
Week 34. |
20% |
Week 36 |
Replication report (class presentation) |
Week 34 |
15% |
The day of the presentation |
Participation |
Weeks 31 and 34 |
5% |
Week 39 |
Replication paper |
Week 36 |
40% |
Week 40 |
- Module Supervisor: Carolina Garriga
- Module Supervisor: Seonghui Lee
- Module Supervisor: Paul Whiteley
- Module Supervisor: Seonghui Lee
- Module Supervisor: Alexandra Hennessy
- Module Supervisor: Laura Sudulich
- Module Supervisor: Royce Carroll
On completing this module, students should have a good understanding of different approaches to ideology and discourse analysis; the ability to engage critically with the key texts and concepts discussed in the module; and the capacity to initiate independent research from a discourse theory perspective.
- Module Supervisor: Jason Glynos
- Module Supervisor: David Howarth
- Module Supervisor: Jason Glynos
- Module Supervisor: David Howarth
- Module Supervisor: Zorzeta Bakaki
Doctoral candidates in the Department carry out their research in a wide variety of areas on a diverse set of topics, using a wide range of different approaches from nomothetic-deductive formal modelling, to quantitative and qualitative comparative studies, to normative political philosophy. Healthy exposure to these different perspectives in the scholarly study of politics provides an opportunity to improve general knowledge and background, and even provide new ideas for specialised areas of research. This seminar is not aimed at any sub-field or methodological tradition in particular.
Inevitably, the primary focus here is the academic profession. We will therefore practise a number of specific skills such as drafting research proposals, presenting results, and publication strategies. However, many of the sessions are also highly relevant for the other kinds of professions in which PhD graduates often find employment. Whatever your target, we aim in this seminar to provide a constructively critical atmosphere in which to hone various skills.
- Module Supervisor: Shane Martin
- Module Supervisor: Zorzeta Bakaki
Weeks 10-11 Students should meet with their division manager to have an informal discussion about their dissertation topic and seek advice about a potential supervisor.
Week 16 Meeting with Graduate Director for all students who will be informed about what is expected from a dissertation and what progress checks have been put in place.
Week 17 Students submit their Dissertation Topic and Nomination of Supervisors form on FASER. They must include their topic and a proposed title. They are also given the opportunity to nominate up to three potential supervisors
Week 19 A supervisor is allocated to the student.
Week 24 Students' must submit on FASER a timetable of what should be completed by when. This must be agreed with the dissertation supervisor.
Week 30 Students' dissertation title must be finalised with their supervisor and they must submit their week 30 progress check form on FASER.
Weeks 30, 32, 37-38 Students must have at least two face-to-face sessions with their supervisor.
Week 38. Students must submit the week 38 progress check on FASER.
Week 38 or 39 a Dissertation Workshop is held. Staff from all four divisions and with expertise in a range of topics and methods will be available for consultation on general dissertation issues and students' own specific questions and problems.
Week 50 Dissertation due on FASER on Friday at 10 am.
- Module Supervisor: Lawrence Ezrow