The document discusses a study that tested how knowledge of previous convictions influences judgments of guilt. It describes two predictions: 1) those with a logical framework will conclude "not guilty" regardless of convictions, while those with a probabilistic framework will conclude guilt is more likely with convictions; and 2) underlying guilt ratings will not/will be increased by convictions depending on the framework. The methodology involved a scenario of a child's death with/without mention of previous convictions. Results showed convictions biased verdicts and guilt ratings, indicating probabilistic rather than logical reasoning. The implications for law and theory are discussed.
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Previous Convictions and Ratings of Guilt in Legal Judgments
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9. Ok, for a moment let’s think about your own research… We will return
to the prior conviction study a little later…
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17. Example from earlier – let’s see…
Previous convictions and underlying ratings of guilt
Testing Theories: Logical v Probabilistic Theoretical Frameworks…
Logic Prediction 1: Participants will conclude that the defendant is ‘not guilty’
regardless of the number of previous convictions.
Probability Prediction 1: Participants will conclude that the defendant is
‘guilty’ or more guilty than chance (.5) when a previous conviction is
present.
Logic Prediction 2: Participants’ underlying ratings of guilt will not be
increased by the presence of previous convictions between the absolute
values of not guilty (zero) and guilt (one).
Probability Prediction 2: Participants’ underlying ratings of guilt will be
increased by the presence of previous convictions, and this increase will
occur between the absolute values of not guilty (zero) and guilt (one).
18. Methodology: The Experimental Method
◼ Participants – Demographics must be representative of jury population…
◼ Mean Age, Gender, etc.
◼ Design: What will your conditions look like?
◼ Example Materials: Reasoning about a scenario created from a real life case
of a child who was killed by a man with two previous convictions for similar
offences.
On January 2, 2006, David Baxter had been arrested. He had been
accused of killing 18-month-old Joanna Connolly. Joanna’s skull had
been fractured when she received a physical blow to the head. She
was the daughter of Susan Connolly, the woman who David Baxter
had been seeing.
19. Materials Template
Knowledge of previous convictions (one; two; none):
David Baxter had previously served a three year sentence for being
physically abusive towards an ex-girlfriend’s three year old girl in 2003.
Please answer the following questions:
Q.1 Please tick whether you think:
David Baxter is guilty __
David Baxter is not guilty __
You cannot decide __
Q.2 On a scale of 1 to 10, circle the number that you think best reflects how
guilty you think David Baxter is:
(0 represents Not Guilty, 10 represents Guilty)
Not | | | | | | | | | | | Guilty
Guilty
20. Method
◼ Seventy-two participants, 24 men and 48 women. Age range 18- 53years,
mean 22.4years
◼ Design 3 x 2 between subjects (left-handedness, right-handedness, no
handedness) x (previous conviction, no previous conviction) [6 conditions]
◼ Materials: The same scenario and measures either with or without a
previous conviction and sort of handedness:
Forensic evidence showed that the blow was delivered by a left-handed
person. David Baxter is left-handed
or
Forensic evidence showed that the blow was delivered by a right-handed
person. David Baxter is right-handed
21. People tend to significantly choose ‘cannot decide’ more often except when a previous
conviction is accompanied by evidence of a left handedness match (PC and LH).
22. Example of a statistic to test the reliability of a trend or difference
(Kruskal Wallis, chi2= 12.282 (5), p <.031).
24. Interpretation of results:
Implications for Law in the Real World and
Implications for Theory too…
◼ Even though on the surface it appears that people cannot decide, their
underlying ratings of guilt are biased by knowledge of previous convictions.
Previous convictions tended to bias verdicts in the presence of small
amounts of confirming forensic evidence.
◼ Perhaps indicating that people reason probabilistically towards logical
conclusions.
◼ Possibly due to similarity (e.g., PC) and not necessarily the result of a lower
probability
◼ Indicating that we next need to understand how the transition from
coincidence to evidence takes place (Griffiths & Tenenbaum, 2006).
34. Example of Critical Appraisal - Crime in England and Wales
Home Office Statistical Bulletin January 2006
◼ The risk of being a victim of crime (23%); lowest since the survey (BCS)
began in 1981
◼ Violent crime is stable compared with the previous year (BCS)
◼ Domestic burglary recorded by the police decreased by 7% (remember this
percentage)
◼ The ‘Dark Figure’ (unreported crime which we will show still exists even in
the 2006 statistics…)
35. Percentage risk of being a victim based on British Crime Survey interviews in the 12 months
to September 2005 compared with the previous 12 months [adapted from the Home Office
Statistical Bulletin, (Kara & Upson, Jan 2006)]. See infographic below:
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10
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25
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Interviews in Oct 2003 to Sept 2004 Interviews in Oct 2004 to Sept 2005
All household crime Domestic burglary All vehicle thefts All personal crime
With injury With no injury All BCS crime
‘All personal crime’ dropped significantly at the p = .05 level, two tail tests
Domestic burglary
did not drop 7%
according to the
BCS! PS. Use
multiple sources of
official statistics…
36. Does some crime ‘disappear’ from official statistics (i.e. police
reports) or ‘remain pending’ from the event to conviction?
Simmons Report (2000)
◼ Step 1. Does the victim notice the crime?
Victimless crime
Unnoticed crime
◼ Step 2. Will the victim report the crime?
Fear (humiliation, being blamed)
Beliefs about police competency
◼ Step 3. Will police record the crime?
Notifiability (e.g., Ford vs Ferrari wing mirror)
Change in policy over time (e.g., Steven Lawrence Inquiry)
Political issues (e.g., Gudjonsson et al., 2004)
Missing persons are in the inquiry stage
Policing decision processes (e.g., malicious accusations)
37. ◼ Step 4. Will the offender be caught?
Not all reported crimes are solved
Decision process (e.g., 15-16yr old shoplifting)
◼ Step 5. Will the offender be prosecuted?
Seriousness of offence
Strength of the evidence (e.g., Billy Jo Jenkins)
Enough evidence to go to trial (i.e., Crown Prosecution Service
decisions)
◼ Step 6. Will the offender be found guilty if he/she is in fact guilty?
Justice is a balancing of many complex considerations
Manslaughter versus Intent