VisualCriminologyASC

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The Rise of Visual Criminology:
Categories, Approaches, and
Testable Propositions
J. Wheeldon
Norwich University
D. Harris
San Jose State University
Today
Why visualize? Who’s visualizing?

Categories and Approaches

Problems

Testable Propositions

Why Visualize?
Assumption: use of and interest in visual
means and methods growing in many
disciplines (Umoquit, Tso, Burchett, &
Dobrow, 2012);

Recognition that people are spending an
increasing amount of time staring at screens,
and engaging visually with their phones,
computers, and social media;

ahem.
Who’s Visualizing?
Criminologists including Burruss (2011), Heidt
(2008), Lippens (2004), and Maltz (2009)?

New Directions in Visual Criminology panel at
ASC;

This work is based on previous work (Harris,
2013; Wheeldon, 2011) and desire to better
define and operationalize what we mean...

One take:
Visual criminology:

Techniques for the collection, presentation,
and interrogation of data on crime and social
control (Wheeldon & Harris, 2013).

Existing categories:



1) exploring research methods through expanded uses
of concept maps, mind maps, and other diagrammatic
approaches in criminology (Wheeldon & Ahlberg,
2012);
2) describing data, telling stories, and presenting
information using visual analytic approaches (Harris,
2013; Maltz, 2009); and
3) demystifying theory, challenging research
assumptions, and interrogating depictions of crime and
social control (Lippens, 2012).
investigations. Glenn Firebaugh (2008) summarizes seven principles for good
science research. These include the possibility of surprise, the need to explore
Learning Research Methods
within your research, the need to compare findings of one group with findings
(Wheeldon & Ahlberg, 2012)
another, and to focus on how, why, and to what extent things change.
Figure 1.1 Seven Rules for Social Science Research
How do the differences between concept maps and mind maps
underscore epistemological, assumptive, and practical differences
between quantitative and qualitative research?
Build in reality
checks
Possibility of
surprise
Compare like
with like
Seven Rules
Differences
matter
Replicate
where possible
Method as a
means
Count change/
Change counts
Existing categories:



1) exploring research methods through expanded uses of
concept maps, mind maps, and other diagrammatic
approaches in criminology (Wheeldon & Ahlberg, 2012);
2) describing data, telling stories, and presenting
information using visual analytic approaches (Harris,
2013; Maltz, 2009); and
3) demystifying theory, challenging research
assumptions, and interrogating depictions of crime and
social control (Lippens, 2012).
Describing Data: In SF Crime doesn’t Climb
(Wintrob &Reinhardt, 2013)
Crime and Neighborhoods in DC
Describing Data: Most Violent Police Beats in
Oakland CA 2011/2012 (Natesh Daniel, 2012)
Existing categories:



1) exploring research methods through expanded uses of
concept maps, mind maps, and other diagrammatic
approaches in criminology (Wheeldon & Ahlberg, 2012);
2) describing data, telling stories, and presenting
information using visual analytic approaches (Harris,
2013; Maltz, 2009); and
3) demystifying theory, challenging research
assumptions, and interrogating depictions of crime
and social control (Lippens, 2012).
Depictions of Crime and Criminals
Images of Crime/Criminals:
Last Suppers (Green, 2012)
So What?
New Visual Approaches...

(1) can provide new ways to teach theory,
methods, and critical debates in criminology;

(2) offer novel approaches to data collection
and analysis; and

(3) create potential for the increased use of
visual tools for practitioners within the
criminal justice system.

Teaching Criminology Theory
(Heidt & Wheeldon, Contract)
7 steps of criminological thinking
Visual Data Collection
Life History Plot (Harris, 2013)
Data Visualization technique

Official criminal history

Life history details (including marriage,
divorce, employment, military,
births/deaths, trauma/ accidents, hospital
stays, and psychiatric observations) were
collected

Life History Plot - Step 1
Life History Plot - Step 2
Life History Plot - Step 3
An Example from Incarcerated Individual
A Picture is Worth a Thousand P- values
Problems / Limitations
Images can confuse and fail to clarify;

Visual learning not for everyone;

No clear definition / conceptualization /
testable propositions

Confusing not clarifying
NYTimes, April 29, 2007
Mapping not for everyone



Potential for maps contains inherent limitation;
Maps and Visual approaches are weird / different /
uncommon way for many to communicate - people
may reject without proper training / explanation
(Wheeldon, 2012)
While maps can assist to break out of the “canned
responses” that can occur in interviews in
Wheeldon’s work some senior CJ officials were
skeptical / resistant to their use;
Thinking about testable propositions
CATEGORY
CHALLENGE
PROPOSITION
Collection
Not everyone is able to
communicate or engage
visually
Visual data collection is as good as
other forms of participant-led data
collection techniques
“Looking at the data” first
can amount to a fishing
expedition (cheating)
Preliminary analysis using
visualization enables the
identification of outliers that warrant
exclusion or further study
Analysis
Presentation
Reducing criminology to a The presentation of criminological
series of “pictures” simplifies findings using visual approaches
complex issues /
allows more people to access and
relationships / findings
understand research
Some Questions

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1. WHAT are the best uses of visual techniques for teaching and
learning criminological concepts?
2. WHERE are visual approaches most useful to supplement existing
data collection methods and research designs;
3. WHEN do images oversimplify issues instead of expanding
criminological thinking?
4. WHY do images of crime and social control overwhelm more
reasoned approaches to criminal justice?
5. HOW can visual approaches expand partnerships and broaden
collaborations?
Other Questions?
Johannes Wheeldon
(jwheeldo@norwich.edu)

Danielle Harris
(danielle.harris@sjsu.edu)

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