Statistics

Scientists Suddenly Discover Men Don’t Understand Women

Dr Brown demonstrates a portable fMRI device.

Dr Brown demonstrates a portable fMRI device.

Men are traditionally thought to have more problems in understanding women compared to understanding other men, though evidence supporting this assumption remains sparse.

So opens the peer-reviewed paper “Why Don’t Men Understand Women? Altered Neural Networks for Reading the Language of Male and Female Eyes” in PLOS One by Boris Schiffer and others.

Schiffer’s proposition is false, and glaringly so. There is abundant, indeed overwhelming evidence that men can’t figure women out but that those strange creatures largely have us brutes pegged. But then this paper was peer-reviewed and peer-reviewed papers only contain propositions which are ardently believed to be true, so what’s going on?

All is well if we understand that Schiffer’s use of “sparse” does not take its plain-English meaning of “thin or lacking”. Instead it means, “unpublished” as in “evidence supporting this obviously true statement remains unpublished.”

We must then forgive Schiffer and his co-authors because scientists are so desperate to publish that they will write about anything, even the obvious as if it weren’t.

So how did Schiffer and pals “discover” that men think differently than women? Maybe hooked them up to a brain-scanning machine and looked for which little gray cells glowed? And then examined the glowing regions for wee p-values which would pass peer review? Well, that’s it.

They grabbed 22 men off the street, asked them a bunch of questions—they said “administered” “instruments”1, but that’s how scientists talk—and then wired them to a machine with a lot of dials and knobs. They showed the men 36 pairs of eyes and then made them “decide which of the two presented words (e.g., distrustful or terrified) best described the emotional/mental state of the person whose eyes were presented.”

The guys also had to guess if the pictures were boy-eyes or girl-eyes (the “sex discrimination task”). What made it science was that, at the start of each round of pictures, they showed the words “‘Emotion’ or ‘Gender'” for precisely “seven seconds” (and not eight seconds). Time to answer was measured.

During the eye-watching, the fMRI machine took pictures of the fellows’ brains. The machines statistically manipulated the hell out of these images (“Bilinear interpolation”, “normalization”, “smoothed with an isotropic Gaussian kernel”, “boxcar function convolved with the hemodynamic response function”, “High-pass filtering with a cutoff frequency of 120 sec”). This alone gave employment to over a dozen people of your author’s bent.

Anyway, this manipulation obviously (it was prayed) had zero influence on the results. At least, any uncertainty in the manipulation was ignored, as is standard practice. Why rock the boat?

Then the real statistical models happened (“repeated measures analysis of variance”, “General Linear Model”, “ANOVAs”, p-values). The central finding is that “men exhibited significantly greater problems recognizing emotion than gender”.

Sorry, make that they had greater problems recognizing words related to emotion. They were able to pick off which eyes were female slightly better. Who could have guessed?

I know what’s on your mind. What of the amygdala? How can any proper paper on neurology fail to mention this most tiny feature of the brain which is said to cause just about everything we say or do? Breath easy: the amygdala is there. Indeed, “right amygdala activation modulated recognition accuracy.” So there.

And not only that, “The finding of heightened right amygdala responses during recognition of male compared to female stimuli might indicate a highly automated and stimulus-driven effect that occurred regardless of different conditions or instructions.” Or it might indicate men like looking at women more than they like looking at men and more than they like figuring which word pair maps to which eyes? Nah.

Besides a few other things, Schiffer also reported that men can tell which male eyes are angry better than they can tell which female eyes are angry (these may have been confused with “cute”). This may be because males spend more of their lives, particularly their formative years, with other males. But that’s the easy way out. A better explanation invokes evolutionary theory. IDing angry eyes

may have been a factor contributing to survival in ancient times. As men were more involved in hunting and territory fights, it would have been important for them to be able to predict and foresee the intentions and actions of their male rivals.


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1An “instrument” is a questionnaire or survey that somebody else used before you.

Thanks to Al and Ann Perrella for alerting us to this subject.

Categories: Statistics

8 replies »

  1. Ah, the eye watching test. This is described here.

    http://www.romankrznaric.com/outrospection/2010/01/30/359

    and here.

    http://www.amazon.co.uk/Essential-Difference-Penguin-Press-Science/dp/0141011017

    I have read the book. It is interesting if somewhat overstated. Take the eye test and see if you are a sociopath. I dare you.

    In other news, a follow up to an earlier article of yours has appeared at WUWT.

    http://wattsupwiththat.com/2013/04/29/how-a-scientist-becomes-a-con-man/

    Follow the ny-times link for the full sordid story.

  2. Can any two people (no matter what their respective genders are) truly be said to understand each other?

    I have enough trouble understanding my self, now you want me to understand someone else? Unreasonable in the extreme.

    😛

  3. My problem with showing pictures of “emotions” is how are they determined to be true? How did the authors obtain genuinely “terrified” or “distrustful” eyes. Maybe some men can simply tell when women are faking it, even in pictures.

  4. I have become inured to the torrent of garbage coming out of the ‘soft sciences,’ indeed most of science as a whole.

  5. The bottom line is this:
    Neither sex understands the other. This bothers women. The men could care less.

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