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Introduction to social science research (Neuman): Summary 2023
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Summary of all exam material for the course Introduction to Social Science Research.
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H1: Why do research?Forms of knowledge:
- Common sense: if something happens to us, you accept it as true. But everyday reasoning
and perceptions are prone to error: overgeneralizations, selective observation, premature
closing (stop gathering when you’ve seen enough and drawing a conclusion), halo effect
(when we see something as more positive, for example if an essay is from a harvard
student it must be good), or false consensus (we are not good at distinguishing what we
believe and what others believe).
- Knowledge of experts: limitations as it stops you from thinking critically and they can just
be plain wrong.
- Knowledge from popular and media messages: limitations as it can lack factual knowledge
and create “hypes” when a problem is not that big.
- Pseudoscience: false science, for example presented in ads.
- Ideologic beliefs: ideologic beliefs are an enclosed system of absolute, certain answers with
few questions. There are implicit assumptions based on moral beliefs or faith. There is little
evidence, and if there is it’s selective.
Scientific rules:
- Universal norms within the community.
o Universalism: the research is based on its content, regardless of who conducted it.
o Organised skepticism: all evidence and contents are questioned and examined
critically.
o Disinterestedness: scientists are neutral, and therefore receptive to any information
that presents itself, also when it’s against their beliefs.
o Communialism: knowledge belongs to everyone and must be shared.
o Honesty: the researcher is honest on everything that they’ve done and why.
- Information is based on social theory (deductive) or uses data to build up social theory
(inductive).
- Most important: data is empirical. That means it is visible with the human senses. Empirical
data is gathered through experimentation and observation. Use of the scientific method
involves making an observation, developing an idea, testing the idea, getting results, and
making a conclusion.
Quantitative Qualitative
Measures objective facts Constructs social reality/cultural meaning
Focus on variables Focus on interactive processes/events
Independent of context Situationally constrained
Separate theory and data Data and theory fused
Statistical analysis Thematic analysis
Many cases Few cases
Researcher detached Researcher involved.
Value free Values present and explicitly mentioned
Select a topic Acknowledge self and context (to identify a
topic)
Focus the question Adopt a perspective
Design the study Design a study and collect, analyse and
interpret data
Collect data Inform others
Analyze data Maybe continue the cycle of designing,
collecting, analysing and interpreting.
Interpret data
Inform others
, H2: types of social research
Dimensions & major types of social research
- Use and audience
o Academic research: primary audience is the scientific community. Goal is to expand
current knowledge. Is theoretical and explanatory in nature. Doesn’t have an
immediate use, wider scope, is curiosity-driven, predicts future phenomena.
o Applied research: addressing a specific concern, mostly to formulate a
solution/prevention/advancement. Most are short term and small scale research. It’s
practical and descriptive in nature. And most are more connected to economical
pursuits/clients as they appear in real world settings to create a solution/prevention
for future problems. Types: evaluation research, action research, social impact
assessment. (needs assessment/cost benefit assessment often part as well).
- Purpose of research
o Explorative: when something is very new, to become familiar with basic facts, settings
and concerns. Formulate and focus questions for future research. Generate new ideas
and hypotheses.
o Descriptive (most SW): when you want to describe a social phenomenon, to present a
specific description of details of a situation, social setting, relationship. Starts with a
well-defined issue and tries to describe it accurately. Focusses on “how” and “who”
questions when reporting on background or context. It creates a set of
categories/classifications. Uses the most data gathering techniques like surveys, field
research etc.
o Explanatory: when things are not new and have a description and goes on to identify
the reason why something occurs. It looks for cases and reasons, to enrich a theory’s
explanation. It links issues to general principles, determines what explanation is best,
or tests a theory’s predictions/principle.
- Within or across cases
o Case study: examining many features of a few cases. Mostly qualitative. Enables us to
link micro-level to the macro-level by investigating the context as well.
o Across case study: examining fewer features of many different cases. Mostly
quantitative.
- Single or multiple points in time
o Cross-sectional: observe a collection of people at one point in time. In this design time
is not a factor. So it could be 2 groups that are examined in different months, but
change is not a factor. Usually in descriptive research. A cross-sectional study can
collect data on one or many characteristics, and can suggest correlational
relationships. Example: study on death penalty views.
o Longitudinal: explaining the pace and pattern of change across several time periods.
o time series: observe different people at multiple times. To observe stability
or change in the features of the units or to track conditions over time.
Example: birth rate data.
o panel: observe the exact same people at two or more times. Can show the
impact of a life event. Example: impact of 9/11 on feelings of
xenophobia/tolerance in the US with the same adults.
o Cohort: observe people who share a specific life experience in a specific
period for multiple points in time. Not the exact same people are studied,
but people that shared a common life event. Example: all people retired in
the same period.
o Case study: observe a small set intensely across time.
- Data collection techniques
o Quantitative data (experiment, survey, nonreactive: content analysis or existing
statistics)
o Qualitative data (field research, historical-comparitive: examining data on events in
the historical past/different societies)
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