Author Archives: sfietze

Academic English Writing (for GLOMO Project)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonathan Mole, Europa-Universität Flensburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Writing an academic text can be a daunting and complex task requiring the knowledge of a range of accepted writing conventions as well as the ability to construct sentences that are idiomatically and grammatically correct. This workshop will take as the starting point the proposals you wrote for your PhD project applications. Individual feedback will be provided on the texts and assistance will be given during the workshop to enable you to self-correct any issues which have been highlighted (structure, understanding, logic, language etc.). Common issues can be discussed and experience shared. Exercise material will be available to show the importance of an awareness of a range of topics including academic style (formality, impersonal and objective language, passive voice, caution, nominalisation); structure at sentence, paragraph and document level; reporting verbs and their forms; coherence and cohesion; and citation and reference styles. Potentially useful links and book recommendations will be provided.

Requirement of students: Please supply your project proposal at least two weeks before the workshop begins.

Recommended literature and pre-reading: None.

You have to register for the 12th International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Kamil Marcinkiewicz, University of Hamburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The case study research is frequently applied in the social sciences. It is particularly popular among political scientists, especially those specialising in area studies. The ubiquity of the case study research contrasts with the scarcity of theoretical reflection on its core methodological aspects. Also, the benefits of comparative analyses are often underestimated. In this course, participants will have an opportunity to learn more about what the case study research is, what are its weakness and strengths and how should we go about the core question in designing a case study: selection of cases. The course combines lectures with practical exercises and discussion of students’ projects.

Requirement of students: Please bring your laptop computer.

Recommended literature and pre-readings:

  • Gerring, J. (2007). Case Study Research: Principles and Practices (pp. 17-63). Cambridge: Cambridge University Press.
  • George, A. L., & Bennett, A. (2005). Case Studies and Theory Development in the Social Sciences (pp. 1-34). Cambridge, MA: MIT Press.
  • Rueschemeyer, D. (2003). Can One or a Few Cases Yield Theoretical Gains? In J. Mahoney and D. Rueschemeyer (Eds.), Comparative Historical Analysis in the Social Sciences (pp. 305-337) Cambridge: Cambridge University Press.
  • Hall, P.A. (2008). Systematic Process Analysis: When and How to Use it. European Political Science, 7(3), 304-317.

You have to register for the 12th International Research Workshop to participate in this course.

Qualitative Comparative Analysis (QCA)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonas Buche, Leibniz University Hannover

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Since the publication of the seminal work “The Comparative Method” by Charles Ragin in 1987, set-theoretic methods and especially Qualitative Comparative Analysis (QCA) have become a common research strategy in the social sciences. Set-theoretic methods analyse cases with regard to the identification of sufficient and necessary conditions and assume set relations to be equifinal, conjunctural and asymmetric. Not least since so-called fuzzy sets have been introduced to the method, there has been a rising interest in QCA as a welcome alternative to both small-n case studies and large-n statistical analyses. In short, QCA is recommended if ‘if…then’ hypotheses are analysed; if the goal is to derive sufficient and necessary conditions; if a comparison is planned; and if there is a mid-sized number of cases (between 10 and 60+).

The course offers a comprehensive introduction to QCA and is both conceptually and technically oriented. It starts off with an overview of the basics of set theory and demarcates QCA as a case-oriented method from both the quantitative and the interpretive-qualitative research paradigm. Through the notion of necessary and sufficient conditions and of truth tables, the single elements are built into the Truth Table Algorithm. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies on how to overcome them are presented. On the third day, the software tool fsQCA will be introduced and applied to published studies.

Requirement of students: No prior knowledge is required. We will use the software fsQCA2.5 which can be downloaded at www.fsqca.com.

Recommended literature and pre-readings:

  • Cebotari, Victor, and Maarten P. Vink (2013). “A Configurational Analysis of Ethnic Protest in Europe.” International Journal of Comparative Sociology, Vol. 54(4), 298-324.
  • Emmenegger, Patrick. (2011). “Job Security Regulations in Western Democracies. A Fuzzy Set Analysis.” European Journal of Political Research, Vol. 50(3), 336-64.
  • Freitag, Markus, and Raphaela Schlicht (2009). “Educational Federalism in Germany. Foundations of Social Inequality in Education.” Governance, Vol. 22(1), 47-72.
  • Schneider, Carsten Q./Wagemann, Claudius, 2012. Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press.
  • Ragin, Charles C., 2008. Redesigning Social Inquiry. Fuzzy Sets and Beyond. Chicago: University of Chicago Press.
  • Goertz, Gary/Mahoney, James, 2012. A Tale of Two Cultures: Quantitative and Qualitative Research in the Social Sciences. Princeton: Princeton University Press.
  • Buche, Antje, Jonas Buche, and Markus B. Siewert. “Fuzzy Logic or Fuzzy Application? A Response to Stockemer’s “Fuzzy Set or Fuzzy Logic?”” European Political Science 15(2): 359-378. (see also chapter 4 in Buche 2017).
  • Buche, Jonas. 2017. “Assessing the Quality of Qualitative Comparative Analysis (QCA) – Evaluation, Improvement, Application”. Hannover: Leibniz Universität.
  • Buche, Jonas. 2017b. “Europeanization of Legislative-executive Relations at the Micro Level – Under Which Conditions Do Swedish MPs Interact with Ministerial Officials?” COMPASSS Working Paper Series 2017-87 (see also chapter 6 in Buche 2017).
  • Buche, Jonas, and Markus B. Siewert. 2015. “Qualitative Comparative Analysis (QCA) in der Soziologie – Perspektiven, Potentiale und Anwendungsbereiche.” Zeitschrift für Soziologie 44 (6):386-406 (see also chapter 2 in Buche 2017).

You have to register for the 12th International Research Workshop to participate in this course.

Spatial Data Analysis

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Timo Friedel Mitze, University of Southern Denmark

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

‘Researchers are increasingly aware of the fact that ‘space matters’. The goal of the applied course is to equip participants with essential knowledge on methods and tools currently available in the field of spatial data analysis with a focus on ‘Spatial Statistics and Spatial Econometrics’. Besides presenting the general logic and methodological foundations of this research field, a distinct focus is set on developing skills to work with applied examples using the software package STATA. This shall enable participants to build up competencies for conducting own empirical projects in the research field.

The course is structured as follows: After a brief introduction of the historical evolution of spatial data analysis, different research settings in economics and related research fields are outlined, which call for the explicit use of spatial estimation techniques. Following this introduction, the concept of the spatial weighting matrix is introduced and statistical approaches to measure and visualize the degree of spatial dependence for a variable under study are presented.

Moving from univariate to multivariate modelling techniques, the course then presents estimation techniques for spatial models and applies this theoretical knowledge to hands-on applications for different datasets. Finally, as an outlook on future research possibilities, state-of-the-art concepts such as spatial panel data models will be presented.

At the end of the course, participants shall be able to detect the degree of spatial dependence in the available data and judge which spatial econometric models are most appropriate given the research question at hand. Moreover, participants will acquire the ability to estimate such models using the software package STATA.

Datasets, STATA do- and ado-files will be provided ahead of the course.”

Requirement of students: Basic knowledge in Stata. You may watch this online tutorial.

Pre-readings:

Recommended literature:

  • Anselin, L. (2010). Thirty years of spatial econometrics. Papers in Regional Science, 89(1), 3-25.
  • Sarafoglu, N., & Paelinck, J. (2008). On Diffusion of Ideas in the Academic World: The Case of Spatial Econometrics. Annals of Regional Science, 42(2), 487-500.

You have to register for the 12th International Research Workshop to participate in this course.

Data Analysis with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Marco Lehmann, UKE Hamburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The course introduces the programming language R used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated in the course of study. The students will then practice with many statistical examples. In addition to statistical functions, the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge in descriptive and inferential statistics. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

Requirement of students: Basic knowledge in descriptive and inferential statistics is recommended.

Recommended literature and pre-readings:

  • Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.
  • Wollschläger, Daniel (2012). Grundlagen der Datenauswertung mit R (2. Aufl.). Berlin: Springer.

You have to register for the 12th International Research Workshop to participate in this course.

Writing Your Literature Review

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Jun.-Prof. Dr. Katharina Stornig, Justus-Liebig-Universität, Gießen and Dr. Paul Vickers, Universität Regensburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

All research, whatever the discipline and however original, draws on existing studies. Any research project necessarily positions itself in relation to existing empirical, theoretical and methodological debates. This course provides practical insight and advice on how to write a literature review (Forschungsstand) providing an overview of the “state of the art”. The course will begin with insights on tips, tricks and tactics for tackling the literature review, including collecting and synthesizing literature, summarizing existing debates, and providing advice on academic writing in English and German. The sessions will also involve group work and focused feedback on individual projects.

Requirement of students: Each participant sends at least one week in advance of the course an extended abstract (Exposé) of their research project.

Recommended literature and pre-readings:

  • Patrick Dunleavy. How to Plan, Draft, Write and Finish a Doctoral Thesis or Dissertation. Palgrave: 2003.
  • Jose L. Galvan. Writing Literature Reviews: A Guide for Students of the Social and Behavioral Sciences. University of Michigan: 2004.
  • Ansgar Nünning/Roy Sommer, Hrsg. Handbuch Promotion. Forschung – Förderung – Finanzierung. Metzler: 2007.

You have to register for the 12th International Research Workshop to participate in this course.

Social Network Analysis

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Raphael Heiberger, University of Bremen

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The rising prominence of social network analysis (SNA) has been mirrored in the development of specialized tools and computer programs for various kinds of networks. This general trend has been enhanced by the current data revolution. Innovative methods to study social networks are often developed in the R-framework. The workshop introduces various R-packages on SNA and enables participants to construct, analyze and visualize network data. First, we will concentrate on the different logic of each package in terms of graph initialization, their general advantages and disadvantages, and how to overcome those differences. After practising how to treat network data in R, we will focus on the utilization of a variety of network measures describing both actor positions and whole networks. Additionally, there exist many built-in algorithms for community detection and network evolution that can be easily applied after the first steps. After a short explanation of the mathematical and theoretical intuition of the concepts in question, we will apply them to multiple empirical examples.

Requirement of students: Experiences with R might be helpful but are not a requirement. The workshop uses RStudio as a development environment. Please install R and RStudio prior to the workshop. To install, follow these steps:

  1. Download the R-installer from https://cran.r-project.org. Select and download the latest installer suitable to your operating system.
  2. Run the installer. Default settings are fine.
  3. Download RStudio https://www.rstudio.com/products/rstudio/download.
  4. Once the installation of R has completed successfully (and not before), run the RStudio installer.
  5. Open RStudio. It should open a window that looks similar to the image attached.
  6. Install R packages required for the workshop. To do that just type in the console install.packages(’MYLIB’) where MYLIB is a placeholder for the various packages we will need, especially:
    igraph
    igraphdata
    statnet
    ergmharris
    intergraph
    reshape2
  7. You can see if the package installation was successful by just loading a package
    with library(MYLIB). Note that there are no quotes now.

Recommended literature and pre-readings:

  • Marin, Alexandra & Barry Wellman (2011): Social Network Analysis: An Introduction. In: John Scott & Peter J. Carrington (Eds.): Sage Handbook of Social Network Analysis. London/New Delhi: Sage, pp. 11-26.
  • Hanneman, Robert A. & Mark Riddle (2011): Concepts and Measures for Basic Network Analysis. In: John Scott & Peter J. Carrington (Eds.): Sage Handbook of Social Network Analysis. London/New Delhi: Sage, pp. 340-370.

You have to register for the 12th International Research Workshop to participate in this course.

Grounded Theory

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Christine Moritz, Feldpartitur GmbH

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The key purpose of this workshop is to offer a comprehensive introduction to Grounded Theory and it is both, theoretically and practically, orientated. First, participants meet the so-called “essentials”: research design; data collection, open/axial/selective coding, categorizing, writing memos and theoretical sampling (the subjects theoretical sensitivity and generating theory will only be touched), then, second, examples might exercise and clarify these concepts. To assist participants to develop valuable and effective research practices, exemplars from current research projects will be assessed and critically reflected. In addition to your registration please submit a brief abstract (1-2 pp.) and answer following questions (en/ger):

  • What is your current status (e.g. PhD student?)
  • What is the focus of your interest in Grounded Theory?
  • What sort of content and what feedback do you expect?

Requirement of students: Brief abstract answering the above-mentioned questions.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.

Qualitative Interviewing

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Sarah Potthoff, Ruhr-University Bochum

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The purpose of this course is to familiarize participants with the basics of qualitative interviewing. The course introduces methodological and practical aspects of different forms of qualitative interviews like guided interviews, narrative interviews and focus groups. How are these different kinds of interviews different, what are their shared fundamentals, and what makes a good interview in which circumstance?

The course covers issues of research design, including the selection of research questions, methods, and sampling strategies. The participants will learn to conceptualize interview guidelines and to conduct interviews – guided as well as narrative interviews. In addition, frequent mistakes in conducting qualitative interviews and challenges of research ethics will be discussed.

Requirement of students: None.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.

Data Analysis with Stata

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich, Hesse State Statistical Office

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Stata is a statistical program package widely used (not only) in the social and economic sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

  • “What You Type is What You Get”: Basic Stata Command syntax
  • Getting (and Understanding) Help within Stata: Stata Built-in Help System
  • Basic Data Management: Load and Save Stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, Change the Structure of your Data
  • Basic Stata Graphics: Scatterplot, Histogram, Bar Chart
  • Working with “Do-” and “Log-” Files

Requirement of students: Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.