Lecture 1
Ontology
➢ The goal of science is to learn about ‘reality’, but what is reality? Is there one reality or
multiple (e.g. as many as there are human beings?)
➢ Ontology is the branch of philosophy (metaphysics) that focuses on these questions
➢ The key ontological question in the social sciences is whether there is an objective reality
outside the perspective of people
Constructivism
➢ Constructivism states that social reality is not the same as physical reality. People create
their own reality through social interactions.
➢ A molecule might exists in reality, outside people’s mind, but something more abstract, such
as culture, only gets meaning in a person’s mind.
➢ Social reality therefore can only be understood as the collection of perspectives in which the
perspective of the researcher is also ‘a perspective’. (‘the problem of the other mind’)
➢ One perspective is not necessarily more valuable than others. The best we can do is ‘describe
as thoroughly as possible the perspectives of individuals’ and the social interactions that binds
or divides them’ (=thick description)
Objectivism
➢ Objectivism is the ontological position that social observations are ‘real’: they exist outside
a person’s mind..
➢ Things such as ‘culture’ or ‘power’ are not only constructs of the mind, but ‘exists’ in the real
world.
➢ Objectivism is the ontological foundation for a positivist or realist epistemology.
➢ Note: not a strict divide, but rather a scale...
Epistemology
➢ Epistemology is ‘s the branch of philosophy concerned with the theory of knowledge, i.e.
nature of knowledge, justification, and the rationality of belief.
➢ Resolves around the classical question: ‘what can I (learn to) know’
➢ A pertinent epistemological question for the social sciences is whether the methods used in
physics are equipped to study people, social interaction, and societies.
➢ We are not going to answer this question here, but it is crucial that you understand that such
questions are critical for the type of more specific methods a researcher (like you) uses.
➢ Or at least, it (partly) explains why this method course is divided in two parts…
Interpretivism
➢ Interpretivism states that there are vast differences between the methods social sciences and
natural sciences rely on.
➢ Interpretivism states that social science should focus on ‘verstehen’ instead of ‘erklären’
(Wilhelm Dilthey)
○ Erklären: Systematically study the conditions for certain events or relations.
○ Verstehen: Trying to understand why events happen or why social relations exist
➢ According to interpretivists ‘verstehen’ is better suited for social science because the
perspective of people is critical in understanding their behavior.
,Positivism
➢ Positivism is the branch in social science which apply elements of the methodology from
natural sciences to explain social phenomenon (but adapted to cope with the social world):
find trends in observable data.
➢ According to positivists social sciences should focus on predicting observable phenomenon
Realism
➢ Realism , in line with positivism, accepts the usefulness of the natural sciences methodology
and accepts that social reality is real and can be systematically studied.
➢ Realism, however, accepts more room for ‘unobservable things’
➢ Realism is much more influential than strict positivism. For example, in political science we
rely on many abstract concepts which cannot be directly observed
➢ Note: again, not a strict divide, but rather a scale...
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Theory and Empirics
➢ In scientific research you deal with theory and empirics
➢ Theories are ideas about how things work. For instance:
○ E = mc2
○ Longer prison sentences lead to less crime
○ Fear for globalization leads people to vote for Donald Trump
➢ Empirics is what we can factually observe in research. For instance:
○ The speed of light which we observe
○ Crime rates across countries
○ Opinion polls on voting behavior
➢ Remember to always separate these in your research (i.e. assignments)!
Induction and deduction
➢ (Almost) every research includes theory and empirics, but where do you start?
➢ Induction means you first observe reality, after which you try to order the results and based
on this you describe a pattern (formulate a theory): mostly used in interpretivism
➢ Deduction means you first think about patterns in reality (‘theorize’) after which you check
(do research) whether the theory makes sense in reality (in the empirical world). Mostly used
in positivism and realism
Quantitative and qualitative research
➢ The first part of the course is about quantitative methods; the second part is a about qualitative
methods
➢ The ‘defining feature’ of quantitative research is that reality is understood and described with
the help of numbers (in statistics) or words (in case studies); in qualitative research reality is
interpreted through the perspective of the researcher and people involved.
➢ Quantitative research is therefore rooted in positivism or realism; yet qualitative research is
(more often) rooted in interpretivism
, ➢ Note: while we do see qualitative research in a positivist/realist tradition, quantitative research
in a constructivist tradition is really rare.
Qualitative research Quantitative research
Theory/empirical reality Induction Deduction
Epistemology Interpretivism Positivism/Realism
Ontology Constructivism Objectivism
Analysis in Words Numbers and words
Inspiration Humanities Natural sciences
Qualitative research Quantitative research
Realism/positivism Common
Very common
Interpretivism Very common Practically non-existent
Criteria for Quantitative research: cross-sectional, longitudinal, and experimental designs
1. Reliability:
If you would replicate research would this lead to a similar outcome?
If research is not reliable, the findings could be random
2. Internal validity:
Is the causal inference claimed in the research valid?
If research is not internally valid, one cannot make a causal claim
3. External validity:
Do the results hold in a different context?
If results are not externally valid, the results do not say much about the ‘real world’
➢ Quantitative research (and the first part of this course) is (are) founded on these three pillars!
➢ On academic conferences we talk about this endlessly
, Design
➢ There are three designs to approach quantitative research: cross-sectional, longitudinal, and
experimental
➢ The first question you therefore should ask yourself when reading research is what is the
design: cross-sectional, longitudinal, and experimental
➢ What makes them different? We look at them in turn…
Cross sectional research
➢ In a cross-sectional design one compares variables in one moment in time.
➢ In a typical cross-sectional design (for instance with voters as the unit of analysis) a large
group of people is surveyed with closed (multiple choice) questions or social reality is coded.
○ E.g.: How positive is your attitude towards migrants on a scale of 1 to 10?
○ E.g.: What is your length?
○ E.g. How democratic is a country
○ E.g. How many war victims are there in a country
➢ Every questions in the survey is a variable: something on which respondents can differ
○ E.g. Attitude towards migrants, height, level of democracy, war victims
➢ Cross-sectional research is often called correlation-research because one looks for
correlations between variables.
○ E.g.: If men are taller than women, this means there is a correlation between gender
and height of people
○ E.g. if there are less war victims in democratic countries this means there is a
correlation between democracy and war victims
Advantages cross sectional designs
➢ High reliability:
○ In a cross-sectional design many people can participate (i.e., a large sample can be
drawn) which increases the chance that findings are random.
○ If you, for instance, find that men are taller than women in a survey of 5000
participants (randomly selected), the chances is very high that if you would replicate
this study you would come to similar results (even if it is a different sample).
➢ High external validity:
○ It is relatively easy to find a representative sample in a cross-sectional design.
○ The participants of the study should share many characteristics with the population,
for instance their age, gender, occupation, opinions, etc.
○ This means that for this type of research, the chances are high that what you find can
be generalized to the population.
➢ But not perfect..
Example of watching television – what is wrong?
➢ You cannot make causal inferences based on this study
➢ Watching television could also be caused by the fact that men watch more television than men
& men have more headaches than women.
➢ In other words, there could be a spurious relation: a statistical correlation without a causal
link.
➢ The advise to people to watch less television is therefore is therefore not right.
