Samenvatting
Summary Course Criminology and Safety.
- Instelling
- Universiteit Utrecht (UU)
Executive summary of the course literature Criminology and Safety (). English written!
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Voorbeeld 3 van de 29 pagina's
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Door: Ari22 • 4 dagen geleden
Voorbeeld van de inhoud
Summary Criminology and SafetyInhoudsopgave
Week 1.......................................................................................................................................................... 2
Science, politics, and crime prevention: Toward a new crime policy (Welsh & Farrington, 2012)......................2
Methodological quality standards for evaluation research (Farrington, 2003)..................................................3
Week 2.......................................................................................................................................................... 6
Situational Crime Prevention: Theoretical Background and current practice (Clarke, 2009)..............................6
General strain theory (Agnew & Brezina, 2019)..................................................................................................9
Control as an explanation of crime and delinquency (Britt & Rocque, 2015)....................................................10
Week 3........................................................................................................................................................ 14
The spreading of disorder (Keizer, Lindenberg & Steg 2008).............................................................................14
Guardians on guardianship: Factors affecting the willingness to supervise, the ability to detect potential
offenders, and the willingness to intervene (Reynald, 2010).............................................................................14
Collective efficacy, neighborhood and geographical units of analysis: finding from a case study of Swedish
residential Neighborhoods (Gerell, 2014)..........................................................................................................15
Week 4........................................................................................................................................................ 17
Understanding cybercrime involvement: a quasi-experiment on engagement with money mule recruitment
ads on Instagram (Bekkers, Moneva & Leukfeldt, 2022)...................................................................................17
Empty Street, Busy Internet: A time-Series Analysis of Cybercrime and Fraud trends during COVID-19 (Kemp
et el, 2021).........................................................................................................................................................19
Week 5........................................................................................................................................................ 20
Terrorist use of the internet by the numbers (Gill et al, 2017)...........................................................................20
Online Extremism: Research Trends in Internet Activism, Radicalization, and Counter-Strategies (Winter et al,
2020)..................................................................................................................................................................21
Week 6........................................................................................................................................................ 25
Does predictive policing lead to biased arrests? Results from a randomized controlled trial (Brantingham,
Valasik & Mohler 2018)......................................................................................................................................25
Reform predictive policing, (Shapiro 2017)........................................................................................................25
Advocate: Technology in policing (Ariel, 2019)..................................................................................................26
1
,Week 1
Science, politics, and crime prevention: Toward a new crime policy
(Welsh & Farrington, 2012).
Crime prevention refers to efforts to prevent crime or criminal offending in the first instance
– before the act has been committed.
It often takes place or is initiated outside of the formal justice system.
Prevention is considered the fourth pillar of crime reduction, alongside the crime-
control institutions of police, courts, and corrections.
Alternative crime prevention strategies:
- Developmental prevention: to prevent the development of criminal potential in
individuals, especially those targeting risk and protective factors discovered in studies
of human development.
- Situational prevention: to prevent the occurrence of crimes by reducing
opportunities and increasing the risk and difficulty of offending.
- Community prevention: to change the social conditions and institutions (e.g.,
families, peers, social norms, clubs, and organizations) that influence offending in
residential communities.
Prevention is no panacea; it does not work for everyone or in every context.
Prevention science strengthened crime prevention
The idea of an alternative, non-punitive response to the prevention of delinquency
and offending is a crucial element in prevention science's mission.
An evidence-based approach to crime policy embraces prevention science's commitment to
the use of the most scientifically valid studies to evaluate programs.
Adds the utilization of accumulated scientific research evidence on effectiveness.
The evidence-based approach has had some interesting influences thus far on how crime
prevention is viewed in the U.S. The Preventing Crime report and its subsequent public and
scholarly attention served to shift the debate away from the perception that support for
crime prevention is tantamount to being soft on crime, which was at the heart of the
opposition to the prevention spending in the Violent Crime Control and Law Enforcement
Act of 1994.
Need to increase the influence of research on policy:
- Evaluation research can exert influence on policy discissions
Crime prevention as soft on crime? Belief systems:
- An entrenched, moralistic views about crime. Here, crime is seen as evil, with
redemption only achievable through extreme state sanctioned deprivations of
liberty, sometimes including even the death penalty. There is no room for
prevention. It is held that the general deterrent effect of harsh sanctions will be
sufficient to persuade others from embarking on a life of crime.
- Politicians think that citizens are punishment-oriented.
Citizens are highly supportive of crime prevention and are even willing to pay more in
taxes to support these programs compared to other responses
Another challenge: that confronts crime prevention, especially developmental and
sometimes community approaches, is that the benefits from reduced crime may not be
apparent for a number of years – at least until children reach adolescence.
Conflicts the short time horizons
2
, A potential remedy is to educate politicians about the many other desirable effects
that these prevention programs can produce in the short-term.
The idea that we should think about government expenditure and revenues as flows
over long periods of time, and make clear to the public the impact that different
policy decisions will have on these long-term flows
A new crime policy
A reduction in the use of imprisonment can lead to a reduction in crime rates.
This is possible, they contend, if the cost savings from this policy change are allocated
to hot spots policing and other effective policing strategies
A new crime policy is needed that strikes a greater balance between prevention and control.
Developmental crime prevention is designed to improve individual functioning across
multiple domains.
Methodological quality standards for evaluation research (Farrington,
2003).
Methodological quality depends on four criteria: statistical conclusion validity, internal
validity, construct validity, and external validity.
Validity: correctness of inferences about cause and effect. To identify plausible alternative
explanations so that researchers can anticipate likely criticisms and design evaluation studies
to eliminate them.
The cause precedes the effect
The cause is related to the effect
Other plausible alternative explanations of the effect can be excluded
Descriptive validity: information about key factors is provided.
Statistical conclusion validity: whether the presumed cause (the intervention) and the
presumed effect (the outcome) are related.
Effect size and their associated confidence intervals and the statistical significance.
Threat: Insufficient statistical power and the use of inappropriate statistical
techniques
The more variability there is, the harder it will be to detect any effect of the
intervention.
Internal validity: the correctness of the key question about whether the intervention really
did cause a change in the outcome.
Most important type
Control condition > experimental control is better than statistical control
Threats: selection (preexisting differences between the conditions), history (event
during the same time), Maturation (trends), Instrumentation (change in method of
measuring), testing (pretest – posttest are different), regression to the mean,
differential attrition (loss of people), causal order.
Randomized experiment has the highest possible interval validity.
Construct validity: the adequacy of the operational definition and measurement of the
theoretical constructs that underlie the intervention and the outcome.
Threats: the extent to which the intervention succeeded in changing what it was
intended to change: treatment fidelity and implementation failure, and the validity
and reliability of outcome measures.
Threat: participants knowledge about the intervention > double blind trials.
External validity: the generalizability of causal relationships across different persons, places,
times and operational definitions of interventions and outcomes.
3
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