Hey all,
As a social science researcher, let me throw in some tips for reading research that I give to all my students:
First, the comment about "statistics" versus "individuals" is true. Statistics provide frequencies and averages. So when they say that the average woman has better facial recognition skills, they are simply giving you a statistical average from probably just one study (although I can vouch for them in that most studies find the same thing). Individual, however, are...well, just that....very individual. You may fall within the norm or you may be what we call a "statistical outlier." In other words, you fall outside the norm
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Be very cautious, however, about accepting their claims as to what might explain why women recognize faces better (on average) than men. They are making what is called a "socio-biological" claim. In other words, they are trying to use an evolutionary claim about females of the species fighting over males of the species, or competing for the best sperm. This claim is hotly debated and has no real definitive weight since, at best, it is based on some observations of certain primates in the wild.
There are other theories that conclude that women have better facial recognition since they are the bearers and watchers of children. We must be able to not only recognize the faces of our children very quickly, but also the voices, etc.
Oh, back to the rules. First rule of reading science: look at their method and their data sample. Who are they testing? How are they testing them? Are their findings consistent with other similar research? If so, how? If not, what makes them different? Oh, and who is paying for the research?
) For example, if the tobacco industry pays for a study that "proves" that smoking is healthy and all other studies show it isn't, are we to believe that all other studies are wrong?
By the way, to the person who said that it has been "proven," this is often a misnomer perpetuated by the media. Science isn't about "proof" because we use statistics. Statistics can never prove anything since they are about probabilities and not proof. Think of it this way, once something has been proven, it doesn't change. We work in probabilities since we never have complete information. The best we can say is something like, in 95% of the cases it will happen this way (with a 2 or 3% chance of error in either direction).
Ack. what a ramble. Anyway, the gist of the research is supported by a lot of other research. The claims about evolution are hotly debatd because they are anyone's best guess about why
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