Lecture 4 Flashcards
What is research design?
Aim of research – to expand boundaries of
existing knowledge
▪ Getting valid answers to research questions in a
reliable and efficient way.
▪ Applied (operational) epistemology – how do we
know?
3 levels generality
Level 1 (comes first)
▪ Ontological, epistemological, broad theoretical
outlook
Level 2
▪ Research goal and question, relation with theory,
conceptualization, operationalization, class of
research methodology (qualitative, quantitative,
both)
Level 3 (comes last) -> cases, variables and evidence
Research questions and research goals
General aim of research:
▪ Advance the ‘state of the art’ (state of existing
knowledge, scientific literature)
Motivation of research question:
▪ Puzzles and lacunae
▪ Substantive problems
Research question and research goals
Firstly, (Scientific) description
Secondly, (Causal) explanation and prediction
Thirdly Understanding/interpretation
▪ Combinations possible! But remember epistemology
and ontology are skins not sweaters
Research goal; scientific description
▪ Analytical dimensions (concepts) often theoretically
informed
▪ Implications for both empirical and normative theory
▪ Comprehensive representation of one / few case(s)
(many variables)
OR
▪ Classification of many cases (one or few variables)
Description goes with classification
▪
‘The value of scientific description is in selecting
a set of important analytical dimensions on
which to project the empirical world’ (LMS 223)
▪ Classifications imposed on the social/political
world
▪ Classification is a first step to theory
Research goal; causal explanations
▪ Associated with foundationalist ontologies = with the
behaviouralist, rational choice, and some Marxist and
institutionalist approaches
▪ Not deterministic in the social sciences, instead probabilistic
▪ If the cause had been different, the outcome would have been
different
▪ Causal mechanism
▪ Strength of causal effect
▪ Retrospective (what was) versus Prospective (what would be)
Research goal; interpretation
Associated with anti-foundationalist ontologies = with
the constructivist and some feminist theoretical
approaches
▪ Interpretivists reject a ‘scientific concept of causation’
(Bevir and Rhodes 2016)
▪ Political actions are the product of subjective reasons,
meanings and beliefs
▪ So we should focus on understanding rather than
explanation (Weber)
▪ And on constitutive rather than causal arguments
(Wendt)
Experimental designs
▪ In experimental designs, researchers can
manipulate the design
▪ They must be able to assign cases to a
‘treatment’ group and a ‘control’ group
▪ That is often not possible in political science,
and may be unethical!
▪ When we cannot set up experiments, political
scientists work with observational designs.
Observational methods
Researchers cannot assign ‘treatment’ and
‘control’ groups.
▪ Researcher does control…
1. Which cases to study
2. How many cases to observe
3. Which features of the cases to observe
4. What (sort of) data to collect (qualitative or
quantitative)
How many cases? Large-N observational
Population = individuals, countries, years, written
content, etc.
▪ Ideal: randomly selected sample of individuals, written
content, etc.
▪ Practice: often convenience samples, purposive
sampling
▪ Researcher does not control ‘treatment’ variation
– Try to measure, and thus rule out, all potentially confounding
variables (which to select = based on theory)
– Try to measure, and thus observe, causal mechanisms
Fewer cases; comparative method
▪ Comparative politics ≠ the comparative method!
▪ The comparative method tends to focus on
small-N case studies
▪ It is the go-to method for much empirical
political science when:
– Experimental methods are not possible (no control)
– Statistical methods are not possible (not enough
data/cases)
Fewer cases; MDSD
Research puzzle about a political phenomenon
(outcome)
1. Literature review / theorizing – identify
potential explanations (conditions)
2. Identify only cases in which the outcome is
present (or not)
3. Going through conditions from literature
review, look for a condition that is present in all the cases
Fewer cases; MSSD
Research puzzle about a political
phenomenon (outcome)
1. Literature review / theorizing – identify
potential explanations (conditions)
2. Identify both positive and negative cases
(outcome present and not)
3. Going through conditions from literature
review, look for a condition on which positive
and negative cases differ
Limitations MSSD & MDSD
▪ There are a small number of cases
▪ The methods are sensitive to case selection /
variable specification
– Different result / conclusion with different
cases?
– Selecting cases to fit theory, instead of to test
theory.
▪ What about interactions between variables?
One case; single case designs
▪ If MSSD and MDSD are not possible (not enough cases,
inadequate prior knowledge of relevant variables) we
go back to single case studies
▪ Comparison still important…
– Compare to concepts
– Compare to wider universe of cases and concepts
▪ Case studies themselves are often descriptive, but
– Contribute to general knowledge
– Contribute to theory generating and theory testing
– Important steps in general approach to further understanding
and explanation
