Evidence for shallow voters, or mere exposure? November 15, 2007Posted by Johan in Applied, Face Perception, Social Psychology.
Picture by Brandt Luke Zorn, Wikimedia Commons
Iacoboni has gotten in trouble recently for some bizarre, non-peer reviewed and much publicised studies investigating voters’ neural reactions to the different presidential candidates. Vaughan noted that it is a little surprising that Iacoboni, who has done some fantastic work, would put his name on such weak research. I couldn’t help but be reminded of a post over at Dr Petra Boynton’s blog on the shameless proposals she has received from marketing companies. Essentially, the business model is that you as a researcher either gather some junk data yourself for handsome compensation, or alternatively, you simply sign off on a ready-made article. It is a credibility-for-cash transaction.
Unfortunately, such spin doctor stories might get in the way of real research on voter behaviour. In the latest issue of PNAS, Ballew and Todorov (2007) report that election outcomes can be predicted from fast face judgements in participants who know neither of the candidates. In other words, to some extent voting behaviour is influenced by quick judgments of appearance – maybe the guy with the better hair really does win. Although this study is very interesting, there are a few shortcomings that will be discussed at the end of this post.
Ballew and Todorov gathered pictures of the winner and the runner-up from 89 gubernatorial races. The pairs were shown to participants, who picked the candidate that seemed more competent (other measures were also used, but I’ll spare you the details). In order to avoid familiarity effects, Ballew and Todorov also included a check for whether the participants recognised any of the candidates. Trials in which the participant did recognise a candidate were excluded. The paper contains three experiments, of which I will cover the first two.
In experiment 1, participants were specifically instructed to base their decision on their gut feeling of which candidate would be more competent. The stimuli were presented for 100 ms, 250 ms, or until the participants responded.
Across all conditions, the competence judgements were significantly above chance (50 percent) in predicting the elected candidate. The three conditions did not differ significantly amongst themselves. Looking across all races, the participants’ averaged “vote” achieved an accuracy of 64 percent in predicting the election outcome. This may seem like a trivial increase over chance, but keep in mind that the participants based this decision on only a very brief exposure to an unfamiliar face. The fact that they could predict the winner suggests that voter behaviour is to some extent determined by the same type of fast, automatic evaluations.
In experiment two, Ballew and Todorov sought to investigate whether this effect could be modulated by the instructions that the participants received. Since Ballew and Todorov are advocating the notion that these judgments are automatic and fast, it becomes important to show that participants gain nothing when they have more time to plan their response. Thus, one group was instructed to deliberate carefully over their decision, and were given no time limits for viewing or responding. A response deadline group viewed the stimulus until they responded, which they had to do within 2 seconds. Finally, the 250 ms condition from experiment 1 was replicated for comparison.
In addition to this, Ballew and Todorov restricted the candidate photos to pairs in which the candidates shared the same gender and ethniticity. This was done since results in experiment 1 indicated that predictions were stronger for such pairs.
As in experiment 1, participants in all conditions were significantly more likely to pick a winning candidate. However, when investigating how each group’s “vote” predicted the election outcome, the deliberation group was not significantly above chance, while the two short-exposure non-deliberation groups were above chance, achieving an average accuracy of 70.9 percent between the two. In other words, careful deliberation and slow responding actually hindered performance.
I think these results are nice, since they offer an explanation for why candidates are so well-groomed (particularly the winners), even though no voter would ever admit to basing their choice on the candidate’s appearance. However, I see two issues with this research. First, although Ballew and Todorov asked their participants to rate competence, was this really what the participants were responding to? Given the fast processing that was necessary in the conditions where the participants performed well, it is perhaps unlikely that they were able to incorporate the instructions. Ballow and Todorov compared the ‘gut feeling’ instructions to a condition where participants were asked deliberate, but unfortunately they confounded the ‘instructions’ variable by giving the participants in the deliberation group unlimited time, in addition to different instructions effectively. It would also have been nice to see a control condition where participants indicated which face was more attractive rather than more competent, to show that participants were responding to something more abstract than attractiveness.
The second problem is more fundamental. Ballew and Todorov used participants from the US who viewed US gubernatorial candidates. In other words, it is likely that participants had been exposed to some of the candidates beforehand. We know from a phenomenon called the mere exposure effect that we tend to like things that we know better. It is not unlikely that winning candidates received more media exposure, so the participants may simply have responded to their increased familiarity with the winning candidate.
Ballew and Todorov tried to control for this by removing trials where the participants reported that they recognised the candidate, but this may be insufficient. Research on the mere exposure effect shows that even subliminal exposure to an object can increase self-rated liking for it. So even if the participants didn’t recognise the face, they may still have been exposed to it, and this may have biased their ratings. You might also think that winning candidates may have gained more exposure simply by acting as governor following the election. However, this account can be ruled out by the third experiment, which I haven’t reported here. Essentially, Ballew and Todorov replicated their findings with voters before an election.
To rule out mere exposure effects more conclusively, Ballew and Todorov would have done well to use candidates from local elections in other countries, where any kind of prior exposure would be more unlikely. You can’t help but feel that in using US voters and US guvernatorial candidates, Ballew and Todorov are sacrificing accuracy of measurement for face validity and impact. It is quite powerful to show that US voters respond this way to US candidates – it drives home the point that this is an effect that likely operates outside of the lab too. That being said, I’m not sure if this is a reasonable trade-off to make.
Finally, it’s worth noting that even if Ballew and Todorov’s results really do measure mere exposure (we would need to carry out more research to confirm that), that doesn’t render the findings invalid. It merely means that the mechanism that brings about the behaviour isn’t fast, automatic judgment of facial features, but fast, unconscious biasing based on prior exposure.
Ballew, C.C., and Todorov, A. (2007). Predicting political elections from rapid and unreflective face judgments. Proceedings of the National Academy of Sciences (USA), 104, 17948-17953.