Lectures Designing Social
Research
Lecture 1: What is science?
Characteristics of scientific research
- Common sense versus science: the truth is out there!
- Science: systematic exploration, testing and validation of knowledge
- Accumulation of knowledge, ‘standing on shoulders of giants’
Way of working in scientific research:
1. Theory – logic explanation or prediction
2. Data collection – observation in a systematic way (methodology)
3. Data analysis – comparing what is logically expected with what is actually observed
How scientific research deals with errors from common sense
(common sense is often wrong)
Error:
1. Inaccurate observations
2. Overgeneralization
3. Selective observation
4. Illogical reasoning
Solution:
1. Measurement devices add precision
2. Replicate a study to make sure the same results are produced each time
3. Make an effort to find cases that do not fit the general pattern (principle of
falsification)
4. Use systems of logic explicitly
Principle of falsification = all knowledge is uncertain; explanations are true until they are
refuted -> Karl Popper, voorbeeld van de Zwaan: ga opzoek naar een zwarte zwaan, als je die
niet kan vinden, dan pas kan je zeggen dat alle zwanen wit zijn; alle kennis die we hebben is
onzeker
Spurious = false, fake correlation
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,The cycle of research
Inductive research = weinig informatie/onderzoek over het onderwerp
Deductive research = er is al veel onderzoek gedaan naar het onderwerp; wij als studenten
gaan vooral en meestal deductive onderzoek doen
Axiom = bouwstenen van het onderzoek; de resultaten van het onderzoek
Problem – lack of knowledge (which can be a problem in practice)
Induction – From specific observations (=empirical research) to the discovery of a pattern
among all the given events (=axiom, theory building).
Deduction – From a pattern that is logically expected (=hypothesis, based on theory) to
observations (=empirical research) that test whether the expected pattern occurs.
Theory and variables
Scientific theory = an interconnected, coherent system of premises which aim to describe,
explain, or predict certain phenomena
3 elements:
o Assumptions: basic ideas about nature of mankind; are never tested
o Model: variables and relations
o Hypotheses: predictions, to be tested
Example: Public service motivation (PSM)
Public Service Motivation (PSM) = an individual's predisposition to respond to motives
grounded primarily or uniquely in public institutions and organizations (Perry & Wise, 1990)
4 Motives:
- a deep desire to make a difference (deelnemen aan iets; willen impact maken)
- an ability to have an impact on public affairs
- a sense of responsibility and integrity
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, - a reliance on intrinsic rewards as opposed to salary or job security (ze willen zichzelf
opofferen om in de publieke sector te werken)
Assumption: people are driven by motives (nature of mankind)
Model:
o Latent Variable: PSM (=sum score, scale, or index)
o 4 dimensions: 4 motives (each dimension is a variable in its own)
Hypothesis:
o As people are driven more by motives 1-4, they will have more PSM
o Employees in public sector organizations will have more PSM than employees
in private sector organizations
Conceptual model
PSM extrinsic
XY
Hypothesis
- A hypothesis is a testable prediction (not a question)
- A hypothesis predicts under which conditions the independent variable (X) will
have a directed effect on the dependent variable (Y), for example:
o As X increases, Y will become smaller
o The more X rises, the larger the chance that Y increases
- Applied to PSM:
o People with higher PSM will work more often in public sector
organizations than in private sector organizations
o Extrinsic rewards (money) will be appreciated less by people with higher
PSM than people with lower PSM (because of higher intrinsic motivation =
mechanism)
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