Language Log is a great blog – often pointing out surprising aspects of the way we communicate in our everyday speech and writing. I find myself pondering some posts for hours.
Last week there was a particularly thought-provoking entry by Penn professor Mark Liberman. I know he’s a good guy because the first time I contacted him I asked him whether all languages employ a word for sexual intercourse as a curse word. He didn’t hang up on me and gave me some great material.
In his post, Liberman summarized a talk by another academic, Sarah Jane Leslie, on a linguistic phenomenon known as generic sentences:
“Generic sentences express generalizations about kinds, such as "tigers are striped", "ducks lay eggs", and "ticks carry Lyme disease"… “Further evidence suggests that these generalizations don't depend solely on information about prevalence. For example, "ticks carry Lyme disease" is accepted, but "books are paperbacks" is not, despite the fact - well-known and acknowledged by participants - that paperbacks are much more prevalent among books than Lyme-disease-carrying is among ticks.”
It’s a fascinating thought. Language can require great inference on the part of the reader or listener. Liberman made the connection to the foibles of journalists who write about science. Now he has my full attention:
I propose a voluntary ban on the use of generic plurals to express statistical differences, especially in talking to the general public about scientific results in areas with public policy implications.
In other words, when we're looking at some property P of two groups X and Y, and a study shows that the distribution of P in X is different from the distribution of P in Y to an extent that is unlikely to be entirely the result of chance, we should avoid explaining this to the general public by saying "X's have more P than Y's", or "X's and Y's differ in P", or any other form of expression that uses generic plurals to describe a generic difference.
This would lead us to avoid statements like "men are happier than women", or "boys don't respond to sounds as rapidly as do girls", or "Asians have a more collectivist mentality than Europeans do" — or "the brains of violent criminals are physically and functionally different from the rest of us". At least, we should avoid this way of talking about the results of scientific investigations.
The reason? Most members of the general public don't understand statistical-distribution talk, and instead tend to interpret such statements as expressing general (and essential) properties of the groups involved. This is especially true when the statements express the conclusions of an apparently authoritative scientific study, rather than merely someone's personal opinion, which is easy to discount.
Read the comments for an amusing series of generalizations about journalists making generalizations.
I completely agree with Liberman on the examples he cited. Those stories and columns felt politically motivated, with the intent of exaggerating sex or racial differences.
Generalizations of this type can be particularly misleading and pernicious in stories about sex differences. If boys test higher than girls on average on their math SATs, it’s not fair to say that “boys are better at math than girls”. Or if more traffic accidents involve men, it’s unfair to say “Men are more reckless than women.”
And yet I think I might have committed this crime myself.
I’m sure I’ve said in the past that the platypus is an egg laying mammal. I don’t have to tell readers that the males don’t lay eggs because you know that. You also know that men don’t suckle babies, and yet the very term “mammal”, coined by great biologist and Carl Linnaeus, applies to both sexes. Yes, he named our whole biological class after boobs, and yet that allowed him to finally correctly classify bats and whales, formerly listed with birds and fish.
These types of generalizations are not misleading because readers understand these are characteristic traits of an animal and apply to one sex. I try to be specific in my writing but I don’t want to waste your time telling you the obvious.
And yet, in Monday’s column on running, I may have quoted someone making the bad kind of generic statement. I briefly addressed the small, persistent gender gap among elite runners. I quoted a biologist attributing it to body fat percentage:
Both sexes are good at distance running, with top women only slightly behind the top men. Lieberman attributes most of the difference to the higher percentage of fat carried by women, which acts as deadweight.
Intuitively I don’t find this misleading, perhaps because there’s no intent here to exaggerate sex differences. I’m just trying to explain what evolution has to do with the human ability to run a marathon. It may be that among elite runners, the sex difference in fat percentage is more than a slight statistical blip. But I may be wrong here.