New research by Blake McKimmie and colleagues (abstract here, full article paywalled) suggests that evidence matters more in criminal cases when the person accused of the crime fits the stereotype of the typical offender.
Mock jurors were asked to determine the guilt or innocence of a defendant accused of robbing a gas station at gunpoint. Half of the mock jurors read a description of the case that relied on weak evidence of the defendant’s guilt (e.g. vague eyewitness accounts) while the other half read a description of the case that included strong evidence (e.g., detailed eyewitness accounts, DNA evidence).
As one would expect, the jurors were much more likely to vote to convict when the evidence of guilt was strong than when it was weak. But this effect only held when the defendant was male and therefore fit the stereotypical image of an armed robber. When the defendant was female, the strength of the evidence was unrelated to jurors’ judgments of guilt.
The authors speculate that when a defendant does not fit a stereotype, jurors attend to the mismatch instead of the specific facts of the case. In the study example, even though women as a whole were not on trial, the jurors tended to focus on the question “Would any woman really be capable of robbing a gas station at gun point?”. This apparently lead them to focus mainly on the defendant’s characteristics relative to the variable that didn’t fit their stereotype (e.g., “Are the signs that she is more aggressive than the average woman?”). This allocation of attention and cognitive effort had the effect of distracting jurors from something which is supposed to be influential in assessments of guilt: The strength of the evidence in the particular case being tried.
It’s an ingenious demonstration of a principle that the psychologists Amos Tversky and Daniel Kahneman explicated so well: When asked a question, our minds will often a substitute a different question before giving the answer, without us being aware of it.
[Cross-posted at The Reality-based Community]
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