Programme
Tuesday, June 23
09:00 – 12:00 | Session 1 – Introduction, Basics and Overview
In the first session, we will discuss how to enter the domain of empirical legal research. The instructors will share what they consider the potential, challenges, and their experiences regarding conducting empirical research in the legal domain.
The second part of the session will be devoted to the basics of empirical research. It will discuss the principles (reliability, validity), research designs (e.g., descriptive, causal), and data collection methods (inquiry, observation, analysis of existing data) of empirical legal research. Participants will then be invited to complete a questionnaire as well as several decision-making exercises. Depending on the pace of the session, the instructors may conduct an interactive game simulating a “dialogue of judges”.
Mini talk – Study presentation (30 minutes)
13:30 – 16:30 | Session 2 – Group Project & Introduction to Python for Legal Research
Groups will be formed for the group project. The substantive part of this session will focus on an introduction to programming in Python. Various statistical packages are available for conducting empirical research. Python has become the most popular programming language to collect, curate, format, and analyse data. Participants are introduced to the basics of the Python language via exercises and assignments. This session will lay the foundation for data analysis later in the course.
Mini talk – Study presentation (30 min)
A shared welcome dinner to kick off the programme together.
Wednesday, June 24
09:00 – 12:00 | Session 3 – Network Analysis
This session focuses on network analysis. Network analysis allows modeling and analyzing connections between different entities: citations, individuals, organizations, etc. In this session, like in the legal field more generally, we will focus particularly on case law citations and litigation networks networks of jurists. Network analysis assists in detecting important precedents and (sub)topics in a network of court decisions. Students will practice collecting, formatting, and analysing real-world data using network science techniques. The instructors will illustrate the methods based on selections from their research.
Mini talk – Study presentation (30 min)
13:30 – 16:30 | Session 4 – Experimental and Observational Methods
This session will be devoted to experiments and observational studies. The randomized trial represents the gold standard in causal inference. Experimental methods are increasingly used in the legal field, notably to evaluate the success of programs or reforms. We will examine different types: vignette experiment, field experiment, and survey.
Rulings, statutes, treaties, and most of what we spontaneously think of as legal data, is observational as opposed to experimental. It is often the only available data, but it presents challenges, particularly when identifying causal relations. In this session, we delve deeper into the advantages and limitations of the analysis of observational data and how to analyse data collected with observational analysis.
The instructors will illustrate the methods based on selections from their research.
Mini talk – Study presentation (30 min)
Details of the programme at the end of the day will be communicated.
Thursday, June 25
09:00 – 12:00 | Session 5 – Textual Methods
Legal data largely come in the form of texts. Advances in automatic text data analysis thus open up great prospects for empirical legal research. We examine document and topic modeling techniques and practice several exercises on texts of decisions of the Court of Justice of the European Union.
Large Language Models (LLMs) like ChatGPT are becoming increasingly popular in analyzing legal texts. In this session, we will explore using LLMs for selected tasks hands-on.
Mini talk – Study presentation (30 min)
13:30 – 16:30 | Session 6 – Group Projects
This session is devoted to the group project. In a hands-on manner, a research plan will be designed and drafted. The instructors will provide feedback on the research designs and envisioned analysis.
A fun shuffleboard evening followed by dinner in the Faculty Garden.
Friday, June 26
09:00 – 10:00 | Session 7 – Data Collection Exercise
Students will participate in a collective data collection exercise. They will look for the raw data and encode it into a structured machine-readable format following a codebook. The results will be presented later during the Summer School.
10:15 – 12:00 | Session 8 – Group Projects
This session is devoted to the group project. The research will be further designed and carried out. The instructors will provide feedback on the research designs and analysis.
13:30 – 16:30 | Session 9 – Legal Data Analysis
Your project will, at this point, have reached the stage of where you are exploring data collection or have started to analyze the data. This session dives deeper into how to conduct empirical analyses. This session will enhance your understanding of which and how statistical analyses can help improve your analysis. This session covers the basics of data analysis, including data harvesting, descriptive statistics, and regression analysis.
An interesting guided tour of the North Caves.
Saturday, June 27 – Sunday, June 28
Session 10 – Group Project Work
Participants continue working independently on their group projects.
Monday, June 29
09:00 – 12:00 | Session 11 – Feedback
Feedback will be provided by the instructors on the group projects.
13:30 – 16:30 | Session 12 – Group Project Work
This session will be devoted to finalizing the project.
Tuesday, June 30
09:00 – 12:00 | Session 13 – Group Project Presentations
Presentation of the group projects.
12:00 | Closing Lunch and Awarding of Participation Certificates
Closing lunch in the heart of Maastricht.