Lecture 1: Introduction to Criminological Research
Notes
Part 1: Quantitative research
Criminological research overview
Criminology = interdisciplinary science with different explanatory models, like
anthropology, sociology, economics, psychology, etc.
The analysis level can differ between micro, meso and macro.
Empirical focus of criminology: direct/indirect observations and experiences.
Quantitative vs qualitative
Quantitative: measuring the size/nature of a phenomenon; testing theory;
generalization. It’s dominant; used the most in science & provides broad data (N=large).
Qualitative: in depth exploration of a phenomenon; building new theories; uncovering
the ‘how’ and ‘why’. This is far less common & provides in-depth data (N=small).
The combination of quantitative and qualitative research methods strengthens research
quality.
Quantitative criminological research = the use of statistical techniques to study crime,
criminal behavior and justice system responses.
- Systematic, empirical investigation of observable phenomena using numerical
data and objective measurement
- Official crime data, non-judicial data, self-report surveys, victim/offender surveys
etc.
- To describe crime trends and patterns
- To test criminological theories using empirical data
- Predict crime occurrences and risk factors.
- Evaluate the effectiveness of criminal justice policies and interventions.
Sampling methods
• Probability sampling = everyone has a known and non-zero chance of being
selected to ensure representative and generalizable results.
• Simple random sampling (500 students selected nationwide)
• Systematic sampling (every 5th student on the list goes into the sample)
• Stratified sampling (separating course rooster into male and female and taking
random samples from each).
1
, • Cluster sampling (choosing 5 random courses and sampling all of the students).
Quantitative research design
Research designs: descriptive, correlational, experimental and
Descriptive: taking a ‘snapshot’ of crime patterns or justice system operations.
- Describe characteristics of offenders, victims, or criminal events.
- Frequency, spatial distribution, population profiling, crime types, time trends,
etc.
- Informs:
o Crime mapping (what crimes and were)
o Resource allocation (policy making to know where to fund)
o Crime reporting (journalists reporting numbers)
o Further research design (can inform quantitative research projects)
- Example: UCR nationwide statistical report of crime data reported by 18.000
agencies & NIBRS is a more detailed system that expanded UCR with detailed
information on each offence in every criminal incident.
- Limitations (lecture): doesn’t investigate what is defined as crime in the first
place (takes crime for granted), doesn’t explain causes (limited analytical value),
only accounts for reported crimes (dark number of crime).
- Limitations (pptx): absent of context (doesn’t explain why crime occurs),
complexity of reality becomes oversimplified, quality depends on accuracy of
data sources, dark number/non-response
Correlational: examines the relationship between two or more variables to determine
whether they are statistically associated.
- Explores risk factors and predictors of criminal behavior.
- Identify important variables using existing data sets:
o E.g. drug use prevalence & property crime incidence (might correlate).
o Just like poverty level & violent crime rate.
- Example: Felson & Cohen’s routine activity approach = emphasizes that crime
occurs when three elements converge: (1) a motivated offender, (2) a suitable
target, and (3) the absence of a capable guardian
o Used official crime statistics to explain crime rate changes in the US
o Independent variables: vacant homes during day, working women, single-
person households.
o Dependent variable: property crime rates.
o Positive correlation found between daytime household absence and
property crime.
- Limitations (lecture): correlation is not equal to causation, results depend on the
data, does not explain why an offender is motivated.
2
, - Limitations (pptx): cannot establish causality, subject to confounding variables
(third variables affecting both), spurious correlations can mislead, does not
explain what motivates the motivated offender.
Experimental: testing causal relationships using randomized control trials.
- Manipulating one variable (independent) to observe the effect on another
(dependent) while controlling for other factors.
- To evaluate whether an intervention can reduce crime, identify causes and effect
between variables, evaluate the effectiveness of criminal justice policies.
- Examples
o Stanford Prison Experiment; students pretending to be guard/prisoner, got
out of hand and was very unethical.
o Milgram’s experiment; give shocks to other people and hearing noise.
o Minneapolis domestic violence experiment: 330 police-handled domestic
violence incidents involving misdemeanor assault → random procedure
to assign one of three responses: arrest the suspect, separate (suspect
from victim) or mediate the situation → measured recidivism → arresting
was the best option to prevent recidivism.
- Limitations (lecture): context is not generalizable, setting is controlled and not
natural, expensive and time consuming.
- Limitations (pptx): low generalizability/external validity, can be expensive and
time-consuming, informed consent and harm? Recidivism is influenced by other
factors (specific for the last example).
Longitudinal: involves collecting data from the same individuals or groups over time,
often across months or years.
- Used to track changes, development, and long-term effects related to crime,
criminal behavior and justice system outcomes.
- Observe patterns over time
- Study causes and consequences of crime
- Test life-course theories of criminal behavior
- Examine how early life experiences relate to later outcomes.
- Example: CSDD followed boys from childhood to adulthood, collecting rich data
to investigate the development of offending behavior across the life course and
risk and protective factors. Key finding: identified ‘chronic offenders’ with early
risk factors and desistance factors.
- Limitations (pptx and lecture): retention over time is challenging, time-
consuming, requires long-term planning and funding, ethical concerns around
confidentiality in long-term tracking (consent can change).
Summary part 1:
3
, - The use of statistical tools and methodologies for analysing crime and developing
strategies for crime reduction.
- Essential role in developing criminological approaches and evidence-based
policies.
- Broad applications in policy and practice.
- Data reliability and validity, sampling issues, ethical concerns.
Part 2: Qualitative research
Main features qualitative research
The qualitative approach is:
• Explorative (no testing) → we don’t know enough, so we explore a phenomenon,
without testing a hypothesis.
• Interpretative (verstehen)
• Constructivist (social, cultural, etc.) → what we know about crime is not based
on experience with crime, but on how e.g. the media presents crime.
• Inductive (data to theory) → you collect data to formulate a theory, instead of
collecting data to test an existing theory/hypothesis (deductive).
• Holistic (all aspects) → not thinking in variables, but broadly seeing phenomena
with al their aspects.
• Contextual (focus ‘in’ context)
• Cyclical and iterative (repeat) → repeating each step many times (not linear
research, but in loops), e.g. reformulating the research question when you
already started conducting your research.
• Primary data (first-hand, fieldwork) → data you collect yourself (secondary data
is collected by others for other purposes).
Why focus on qualitative methods in criminology?
- The ‘why’ question still remains.
- Experiments are difficult or impossible in criminology
- Official crime statistics are limited (dark number) and politically loaded (crime
numbers = hot issues).
- Survey data on sensitive topics: gap between attitudes (words) and social
practices (deeds), e.g. human trafficking victims do not see themselves as
victims.
- Unrecorded fields such as organised, corporate, white collar and state crime.
Also group or gender violence, fraud, drug trafficking and use, green or digital
crimes, etc.
Qualitative designs
• Ethnography (small groups, thick descriptions, Verstehen)
4
Notes
Part 1: Quantitative research
Criminological research overview
Criminology = interdisciplinary science with different explanatory models, like
anthropology, sociology, economics, psychology, etc.
The analysis level can differ between micro, meso and macro.
Empirical focus of criminology: direct/indirect observations and experiences.
Quantitative vs qualitative
Quantitative: measuring the size/nature of a phenomenon; testing theory;
generalization. It’s dominant; used the most in science & provides broad data (N=large).
Qualitative: in depth exploration of a phenomenon; building new theories; uncovering
the ‘how’ and ‘why’. This is far less common & provides in-depth data (N=small).
The combination of quantitative and qualitative research methods strengthens research
quality.
Quantitative criminological research = the use of statistical techniques to study crime,
criminal behavior and justice system responses.
- Systematic, empirical investigation of observable phenomena using numerical
data and objective measurement
- Official crime data, non-judicial data, self-report surveys, victim/offender surveys
etc.
- To describe crime trends and patterns
- To test criminological theories using empirical data
- Predict crime occurrences and risk factors.
- Evaluate the effectiveness of criminal justice policies and interventions.
Sampling methods
• Probability sampling = everyone has a known and non-zero chance of being
selected to ensure representative and generalizable results.
• Simple random sampling (500 students selected nationwide)
• Systematic sampling (every 5th student on the list goes into the sample)
• Stratified sampling (separating course rooster into male and female and taking
random samples from each).
1
, • Cluster sampling (choosing 5 random courses and sampling all of the students).
Quantitative research design
Research designs: descriptive, correlational, experimental and
Descriptive: taking a ‘snapshot’ of crime patterns or justice system operations.
- Describe characteristics of offenders, victims, or criminal events.
- Frequency, spatial distribution, population profiling, crime types, time trends,
etc.
- Informs:
o Crime mapping (what crimes and were)
o Resource allocation (policy making to know where to fund)
o Crime reporting (journalists reporting numbers)
o Further research design (can inform quantitative research projects)
- Example: UCR nationwide statistical report of crime data reported by 18.000
agencies & NIBRS is a more detailed system that expanded UCR with detailed
information on each offence in every criminal incident.
- Limitations (lecture): doesn’t investigate what is defined as crime in the first
place (takes crime for granted), doesn’t explain causes (limited analytical value),
only accounts for reported crimes (dark number of crime).
- Limitations (pptx): absent of context (doesn’t explain why crime occurs),
complexity of reality becomes oversimplified, quality depends on accuracy of
data sources, dark number/non-response
Correlational: examines the relationship between two or more variables to determine
whether they are statistically associated.
- Explores risk factors and predictors of criminal behavior.
- Identify important variables using existing data sets:
o E.g. drug use prevalence & property crime incidence (might correlate).
o Just like poverty level & violent crime rate.
- Example: Felson & Cohen’s routine activity approach = emphasizes that crime
occurs when three elements converge: (1) a motivated offender, (2) a suitable
target, and (3) the absence of a capable guardian
o Used official crime statistics to explain crime rate changes in the US
o Independent variables: vacant homes during day, working women, single-
person households.
o Dependent variable: property crime rates.
o Positive correlation found between daytime household absence and
property crime.
- Limitations (lecture): correlation is not equal to causation, results depend on the
data, does not explain why an offender is motivated.
2
, - Limitations (pptx): cannot establish causality, subject to confounding variables
(third variables affecting both), spurious correlations can mislead, does not
explain what motivates the motivated offender.
Experimental: testing causal relationships using randomized control trials.
- Manipulating one variable (independent) to observe the effect on another
(dependent) while controlling for other factors.
- To evaluate whether an intervention can reduce crime, identify causes and effect
between variables, evaluate the effectiveness of criminal justice policies.
- Examples
o Stanford Prison Experiment; students pretending to be guard/prisoner, got
out of hand and was very unethical.
o Milgram’s experiment; give shocks to other people and hearing noise.
o Minneapolis domestic violence experiment: 330 police-handled domestic
violence incidents involving misdemeanor assault → random procedure
to assign one of three responses: arrest the suspect, separate (suspect
from victim) or mediate the situation → measured recidivism → arresting
was the best option to prevent recidivism.
- Limitations (lecture): context is not generalizable, setting is controlled and not
natural, expensive and time consuming.
- Limitations (pptx): low generalizability/external validity, can be expensive and
time-consuming, informed consent and harm? Recidivism is influenced by other
factors (specific for the last example).
Longitudinal: involves collecting data from the same individuals or groups over time,
often across months or years.
- Used to track changes, development, and long-term effects related to crime,
criminal behavior and justice system outcomes.
- Observe patterns over time
- Study causes and consequences of crime
- Test life-course theories of criminal behavior
- Examine how early life experiences relate to later outcomes.
- Example: CSDD followed boys from childhood to adulthood, collecting rich data
to investigate the development of offending behavior across the life course and
risk and protective factors. Key finding: identified ‘chronic offenders’ with early
risk factors and desistance factors.
- Limitations (pptx and lecture): retention over time is challenging, time-
consuming, requires long-term planning and funding, ethical concerns around
confidentiality in long-term tracking (consent can change).
Summary part 1:
3
, - The use of statistical tools and methodologies for analysing crime and developing
strategies for crime reduction.
- Essential role in developing criminological approaches and evidence-based
policies.
- Broad applications in policy and practice.
- Data reliability and validity, sampling issues, ethical concerns.
Part 2: Qualitative research
Main features qualitative research
The qualitative approach is:
• Explorative (no testing) → we don’t know enough, so we explore a phenomenon,
without testing a hypothesis.
• Interpretative (verstehen)
• Constructivist (social, cultural, etc.) → what we know about crime is not based
on experience with crime, but on how e.g. the media presents crime.
• Inductive (data to theory) → you collect data to formulate a theory, instead of
collecting data to test an existing theory/hypothesis (deductive).
• Holistic (all aspects) → not thinking in variables, but broadly seeing phenomena
with al their aspects.
• Contextual (focus ‘in’ context)
• Cyclical and iterative (repeat) → repeating each step many times (not linear
research, but in loops), e.g. reformulating the research question when you
already started conducting your research.
• Primary data (first-hand, fieldwork) → data you collect yourself (secondary data
is collected by others for other purposes).
Why focus on qualitative methods in criminology?
- The ‘why’ question still remains.
- Experiments are difficult or impossible in criminology
- Official crime statistics are limited (dark number) and politically loaded (crime
numbers = hot issues).
- Survey data on sensitive topics: gap between attitudes (words) and social
practices (deeds), e.g. human trafficking victims do not see themselves as
victims.
- Unrecorded fields such as organised, corporate, white collar and state crime.
Also group or gender violence, fraud, drug trafficking and use, green or digital
crimes, etc.
Qualitative designs
• Ethnography (small groups, thick descriptions, Verstehen)
4
