DESIGNING SOCIAL RESEARCH
Lecture 1
14-02-2023
Scientific knowledge is true knowledge. Other forms of research, for instance journalism, are limited
Less restrictions than in scientific research.
The knowledge does not necessarily have to be of practical use.
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 to deal with errors from common sense
1. Inaccurate observations
--> measurements devices can add precision
2. Overgeneralisation
--> replicate a study to make sure the same results are produced each time
3. Selective observation
--> make an effort to find cases that do not fit the general pattern
4. Illogical reasoning
--> use system of logics explicitly (can these findings be repeated in a different experiment?)
Not coincidental --> systematic
Principle of falsification = all knowledge is uncertain; explanations are true unless they are refuted
A problem in academic research is not necessarily problematic.
Inductive = not enough theory available to build on, observing the problem
Deductive = theory is valready available, researchers can build on this knowledge. Deductive research
can be used to add on to theory or refine it.
Axioms = building blocks of theory
,Scientific theory = an interconnected coherent system of premises which aim to describe, explain or
predict certain phenomena.
3 elements of scientific theory:
- Assumptions: basic ideas about nature of mankind, never tested
Example: people are driven by motives
- Model: core of the theory, variables and relations
Example: PSM, 4 Motives of PSM
- Hypotheses: predictions, to be tested
Example: as people are driven more by motives 1-4, they have more PSM
Public Service Motivation (perry & wise, 1990) = an individual's predisposition to respond to motives
grounded primarily or uniquely in public institutions and organisations
4 motives: sense, reliability, desire, ability
- A deep desire to make a difference
- An ability to have an impact on public affairs
- Sense of responsibility, integrity and compassion
- A reliance on intrinsic rewards as opposed to salary or job security
X = independent variable
Y = dependent variable
Example: insects as new sushi
4 variables --> presentation, migration, taste, convenience, affordability, price
Two elements:
1. Aim --> to acquire more knowledge
2. Question --> topic of research
- Main/central question
- Sub questions
Sub questions can be used to give structure to research.
Criterion of parsimonity: no more or less subquestions than needed to answer the main question
Lecture 2
21-02-2023
Operationalisation = what is going to be researched and what theoretical variables should be used to
measure it?
, There are three steps:
1. Definition --> given in theory
2. Choosing indicators (operationalisations) for variables. These can be dependent, independent
and control variables
3. Determine the values of the indicators (qualitative or quantitative)
Example of operationalisation: social class
1. Definition = a grouping of individuals, based on similar social factors like wealth, income,
education and occupation.
2. Indicators and values = monthly income after taxes, level of education, employment
Unit of analysis -> grouping
Unit of observation -> individual
There are different levels of measurement:
1. Nominal – no ranking possible
- List of political parties, self-identification
2. Ordinal – values increase but not as equal intervals
- Totally agree, totally disagree etc
3. Interval – values increase at equal intervals, there is no reference point
- scale of richter
4. Ratio – values increase at equal intervals with a reference point
- income and age
Facts on operationalisation:
Operationalizing should be done before choosing research methods
(=HOW are you going to study?).
Operationalizations are not the same as items in a questionnaire or
questions in an interview!
Scales and indices, what are they?
Both are used to make connections between observations that are related --> concerning the same
variables. This enables researchers to reduce large amounts of data to one score, which eventually
makes interpretation of results easier.
Index = sum of parts which are logically connected. It turns multiple scores into one.
Scale = sum of parts that are logically and empirically connected. A scale measures the intensity of the
composite.
Two well-known examples:
1. Likert scale: answer range from totally disagree to totally agree
2. Guttman scale: answers (often yes or no) are added to one total score
