Seminar on causal research in social sciences

Teacher(s)

Bocquier Philippe; Rizzi Ester Lucia;

Language

French

Main themes

The seminar starts with an in-depth and detailed discussion on the research methods in social sciences:

• method of synthesis of the literature
• definition of complex concepts,
• causality
• formulating hypotheses
• building of indicators

Each stage is considered according to three big approach data analysis: the statistical approach for the quantitative data stemming from big inquiries; the qualitative approach for the narrative data stemming from detailed conversations, from focuses group or from the participating observation; the mixed approach.

Learning outcomes

At the end of this learning unit, the student is able to :
1.	acquire a critical approach to scientific literature ;
2.	define research questions based on the scientific literature ;
3.	build conceptual frameworks ;
4.	study thoroughly a population issue ;

Content

General objective: to relate research questions and hypotheses to data and method.
Around the research themes chosen by the students for their research dissertation, and based on the review of the scientific literature, the seminar allows us to reflect on:
- data: metadata, datasets, search for existing data, data quality assesment, Data Management Plan. 
- methods: adequacy with respect to hypotheses, assumptions and limits (selection effects, endogeneity of variables ...)
- empirical model (causal diagram): choice of dependent and independent variables, hypotheses on the relationship between these variables.
The aim of the seminar is indirectly to perfect the students' written and oral scientific communication.
The seminar will focus on the stages of construction of the research methodology:
- Identification of the research question and hypotheses (see LSPED2040 and LDEMO2130)
- Identification of data sources
- Identification of data analysis methods
- Construction of an empirical causal schema

Teaching methods

- Introductory presentations provide general methodological principles for developing a demographic research project, illustrated with examples.
- Using introductory presentations and appropriate references, students prepare written work for the next time (i.e. 9 intermediate works + oral presentation).
- At each lecture, professors return to the work presented at the previous lecture by discussing their strengths and weaknesses.
- The final oral presentation sets a deadline for the individual research work and help prepare the methodological chapter that will be the subject of the Master's dissertation.

Evaluation methods

Individual assignments (total of 40 out of 100) must be submitted to both course holders via Moodle by the stated deadlines (i.e. by midnight on the preceding Sunday). Each day of delay will result in a one-point deduction from the mark (see attached calendar):

• Prepare for a round table a 3-minute presentation: research question, hypotheses, mention data and methods (not graded)
  
• Write a one-page presentation of the research question, hypotheses, data and dissertation methods, taking into account the comments and discussion of the previous session (5 pts)
  
• Provide a synthesis of your data search strategy, metadata, and data quality (5 pts)
  
• Draft a data management plan (5 pts)
  
• Present your dependent variable in relation to the research question (5 pts)
  
• Present your envisaged independent variables in relation to the research hypotheses (5 pts)
  
• Present, in the form of an empirical diagram, the relationships between variables from a good reference article (5 pts)
  
• Present possible interactions and strategies to control them (5 pts)
  
• Using two articles as examples, present the method chosen to analyse your data (5 pts)
  

A provisional report will be evaluated through peer review (total of 5 out of 100).
The final written report (total of 55 out of 100): methodological chapter of your dissertation, structured as follows:

• Reminder of the research question and hypotheses
  
• Brief methodological literature review (at least 5 references)
  
• Empirical causal diagram and comments on causal relationships
  
• Data sources envisaged to answer the research question
  
• Methods of data analysis envisaged to test the causal relationships
  

Assessment criteria:

• Conformity with the approach taught (10 pts)
  
• Critical approach to the methodology employed (15 pts)
  
• Originality and relevance of the arguments (15 pts)
  
• Clarity (written expression and logical flow of ideas) (10 pts)
  
• General presentation (titles, references, graphs, etc.) (5 pts)
  

IMPORTANT:

• Continuous assessment cannot be retaken in the resit (second session); the mark for the final report in the second session replaces that of the first session, while the continuous assessment marks are carried over to the second session.
  
• The use of artificial intelligence is not prohibited but must comply with the rules set out in the ESPO Faculty’s note on the subject, available on its intranet site for students: http://uclouvain.be/consignes-chatgpt.
  

Other information

Seminar reserved for 2nd year Masters students in the social sciences preparing a dissertation with a quantitative component.

Online resources

Presentations and other resources are available on MoodleUCL.

Bibliography

Guillaume Wunsch (1988) Causal Theory and Causal Modeling
Chaire Quételet (1987) L’explication en sciences sociales - La recherche des causes en démographie.
Federica Russo (2009) Causality and Causal Modelling in the Social Sciences
Creswell J.W. (2003), Research Design : qualitative, quantitative et mixed methods.
Quivy et Van Campenhoudt (2006), Manuel de Recherche en Sciences Sociales.

Faculty or entity

> PSAD