[This post was co-authored with Jelte Wicherts]
In his well-read blog post, originally titled "Why Black Women Are Less Physically Attractive Than Other Women", psychologist Satoshi Kanazawa from the London School of Economics (LSE) concluded that he had found that African American women were "objectively" less attractive than European American, Asian American, and Native American women. The immediate and far-reaching responses to his controversial conclusions led Psychology Today to first change the blog's title and later to retract it altogether.
Within a few days after the post appeared on the site, a firestorm ensued. Bloggers from all over the world expressed their outrage at the post. Many people's responses were emotionally charged, and rightly so. Many African American women, who must experience discrimination all their lives, were upset and hurt. Other critiques attempted to be analytical, but didn't address the key issues, or attacked the entire field of evolutionary psychology because of one member of the discipline (see my thoughts on that here). The largest student organization in London (representing 120,000 students) demanded Kanazawa's discharge from LSE. According to its spokesman, LSE has started an internal investigation into the blog, although the LSE spokesman stressed the academic freedom of its researchers.
We agree that scientists should not be sacked for making impolite statements that may offend people. However academic freedom does not entail the right (1) to misinterpret data and (2) to ignore empirical findings that go against stated claims.
We retrieved the data from Add Health on which Satoshi Kanazawa based his conclusions to see whether his results hold up to scrutiny. Add Health is a study conducted on a nationally representative sample of adolescents in grades 7-12 who have been followed up to adulthood. The study includes many, many variables (over 8000 in the publically available data sets alone), including measures of social, economic, psychological, and physical well-being. When we first opened the dataset, we were overwhelmed with variables! (One thing we can thank Kanazawa for is even raising this question in the first place, as we probably would not have normally ever looked at the variables he did. Additionally, it must be noted that with so many variables, there are bound to be many statistically significant results in the dataset simply due to chance [1].)
Once we finally located the relevant variables, we conducted the relevant analyses and here's what we found:
1. Kanazawa mentions several times that his data on attractiveness are scored "objectively". The ratings of attractiveness made by the interviewers show extremely large differences in terms of how attractive they found the interviewee. For instance the ratings collected from Waves 1 and 2 are correlated at only r = .300 (a correlation ranges from -1.0 to +1.00), suggesting that a meager 9% of the differences in second wave ratings of the same individual can be predicted on the basis of ratings made a year before [2]. The ratings taken at Waves 3 and 4 correlated between raters even lower, at only .136-- even though the interviewees had reached adulthood by then and so are not expected to change in physical development as strongly as the teenagers. Although these ratings were not taken at the same time, if ratings of attractiveness have less than 2% common variance, one is hard pressed to side with Kanazawa's assertion that attractiveness can be rated objectively.
The low convergence of ratings finding suggests that in this very large and representative dataset, beauty is mostly in the eye of the beholder. What we are looking at here are simple ratings of attractiveness by interviewers whose tastes differ rather strongly. For instance, one interviewer (no. 153) rated 32 women as looking "about average," while another interviewer (no. 237) found almost all 18 women he rated to be "unattractive." Because raters differ strongly in terms of how they rate interviewee's attractiveness and because most of them did numerous interviews and ratings, this source of variation needs to be taken into account when testing for average race differences in ratings of attractiveness. Kanazawa does not indicate that he did so.
2. Kanazawa interprets his findings in terms of adult attractiveness yet the majority of his data were based on the ratings of attractiveness of the participants when they were teenagers. If many of us (including the authors of this post) were judged throughout our lives based on our physical attractiveness as a teenager, a lot of us would be in trouble!
Add Health currently has four "waves", or phases. Here is a chart of the four waves and the age groups of the four waves:
Note that only Wave IV actually consists of "Adults". In fact, the range of ages for Wave I and Wave II is 12-22, with an average age of about 16 for both waves.
Imagine the scenario. Adult researchers (unfortunately we couldn't find out information about the actual interviewers themselves) went into the homes of these participants and rated their own subjective view of the physical attractiveness of the study participants on a scale from 1 to 5 (ranging from "very unattractive" to "very attractive"). For Waves I and II in particular, the ratings couldn't possibly (we hope!) be referring to ratings of the sexual attractiveness of these kids. So discussions of this topic using data from the dating website OK Cupid really aren't appropriate here.
Only in Waves 3 and 4 were the participants old enough on average (M = 22.2, SD = 1.9 and M= 29.00 SD = 1.8, respectively) to be actually called "women" and "men" instead of girls and boys. If one looks at the data from the waves (3 and 4) in which all of the interviewees reached legal adulthood, the pattern of results no longer supports Kanazawa's main conclusion.
In Wave 3, we did find a very slight difference in attractiveness ratings in favor of European women, but this is effect is no longer significant after we take into account the random variation due to the raters.
However, only data from Wave 4 is relevant for the issue that Kanazawa wants to address simply because this is the only Wave consisting of adults (they were collected when all of the participants were adults aged 25-34). Unfortunately, Kanazawa does not include presentation of these Wave 4 results, despite the fact that he uses Add Health data in most of his studies and these data have been available for over a month.
Focusing just on Wave 4, it is obvious that among the women in the sample, there is no difference between the ethnicities in terms of ratings of physical attractiveness. Differences in the distributions for females when tested with a regular (and slightly liberal) test of independence is non-significant and hence can be attributed to chance (Pearson's Chi-Square=15.6, DF=12, p =.210). Here's the graph that shows the distribution of ratings (in percentages) for 1564 European Americans, 553 African Americans, 97 Native Americans, and 96 Asian American females (with arithmetic means below each group):
