Hey—here’s some ridiculous evolutionary psychology for you, along with some really bad data analysis.

Jonathan Falk writes:

So I just started reading The Mind Club, which came to me highly recommended. I’m only in chapter 2. But look at the above graph, which is used thusly:

“As figure 5 reveals, there was a slight tendency for people to see more mind (rated consciousness and capacity for intention) in faster animals (shown by the solid sloped line)—it is better to be the hare than the tortoise. The more striking pattern in the graph is an inverted U shape (shown by the dotted curve), whereby both very slow and very fast animals are seen to have little mind, and human-speeded animals like dogs and cats are seen to have the most mind. This makes evolutionary sense, as potential predators and prey are all creatures moving at roughly our speed, and so it pays to understand their intentions and feelings. In the modern world we seldom have to worry about catching deer and evading wolves, but timescale anthropomorphism stays with us; in the dance of perceiving other minds, it pays to move at the same speed as everyone else.”

Wegner, Daniel M.; Gray, Kurt. The Mind Club (pp. 29-30). Penguin Publishing Group. Kindle Edition.

That “inverted U shape” seems a bit housefly-dependent, wouldn’t you say? And how is the “slight tendency” less “striking” than this putative inverse U shape?

Yeah, that quadratic curve is nuts. As is the entire theory.

Also, what’s the scale of the x-axis on that graph? If a sloth’s speed is 35, the wolf should be more than 70, no? This seems like the psychology equivalent of that political science study that said that North Carolina was less democratic than North Korea.

Falk sent me the link to the article, and it seems that the speed numbers are survey responses for “perceived speed of movement.” GIGO all around!

22 thoughts on “Hey—here’s some ridiculous evolutionary psychology for you, along with some really bad data analysis.

    • Of course they are! (From the linked original article)

      “[A] curve-fitting regression yielded a significant quadratic model (R2 = .37), F(2, 14) = 5.06, p .05, in which mind attribution varied as an inverse quadratic function of speed of motion (beta = -3.93), t(16) = 2.42, p = .03…. A linear regression on nonhuman animal targets, including both targets’ absolute derivations from human movement…, R2 = .78, F(2, 14) = 6.09, p = .01, revealed that the targets’ absolute deviations from human movement predicted the targets’ mean mind scores, beta = 0.54, t(16) = 3.30, p = .005”

      • That quote is cut up wrong. The linear regression you quoted was for a model including “brain weight”. They saw the coefficient for the linear model was not significantly different from zero:

        For these targets, a curve-fitting regression yielded a significant quadratic model (R^2 = .37), F(2, 14) = 5.06, p < .05, in which mind attribution varied as an inverse quadratic function of speed of motion (Beta =-3.93), t(16) = 2.42, p = .03, but did not fit a linear model (R^2 = .06), F(1, 16) = 1.08, p = .32.

        Anyway, shouldn’t the data *not* differ significantly from a good model? They don’t actually test their models. The correct conclusion is that both the linear (even a flat line) and quadratic models are consistent with the data.

  1. From the footnote: mean human speed = 68

    I think that would make a race between a squirrel and a human about a wash, with maybe a small edge to the squirrel. Sounds…ummm… wrong?

  2. I wonder what the graph would look like with peak momentum, not (perceived) velocity, on the x axis. Or maybe kinetic energy… then they could probably get their mammalian supremacy without wackadoo model fits.

  3. Re “housefly-dependent”, a term which I, too, like: I tell students that if the visual “pattern” in a scatterplot can be eliminated by putting your thumb over one of the points, then you don’t have much of a pattern. I learned this as the “thumb test”, although I don’t know if that term is at all widespread. It’s a quick visual way of suggesting a data point with high, perhaps too high, influence. The housefly is such a point.

  4. In general, I think insects move fast relative to their size. if you simply add more insects (which generally are not thought of as “exhibiting mind”) , it would buttress their conclusion.

    Alternatively, they’re model basically says, we hold mammals above other animals in esteem, but not enough not to eat them.

    • It’s literally “God of the Gaps” except they cram the word “evolution” instead. It’s embarrassing.

      Also, I see at least a 7th degree polynomial there, and a discontinuity or two. Why stop!?

  5. Never mind the graph – that whole paragraph is bizarre. How are dogs and cats “human-speeded”? How are our predators and prey only restricted to animals around the same speed as us? Near the end they seem to treat “mind attribution” and “understanding intentions and feelings” as synonymous phrases, which I guess it could be true given how vague “mind attribution” is, but still feels wrong.

  6. I wonder how many subjects have ever met most of those animals? I am very familiar with cows but I have only seen kangaroos once and they were about 100m away.

    Let me assure you a cow can be very fast in real life.

  7. From the linked article: “A perceiver gains little reading the mind of a target moving much faster than the
    self. Such a target cannot be avoided or caught, so there is no use in speculating about its mental states in order to predict its actions. Instead, it is better to respond to such agents by some fixed rule (e.g.,
    “Play dead!” or “Run away!”).

    You gotta watch out for those hummingbirds and houseflies.

Leave a Reply

Your email address will not be published. Required fields are marked *