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This is a world where things move at their own pace, including a tiny lift Fortey and I shared with a scholarly looking elderly man with whom Fortey chatted genially and familiarly as we proceeded upwards at about the rate that sediments are laid down. When the man departed, Fortey said to me: "That was a very nice chap named Norman who's spent forty-two years studying one species of plant, St. John's wort. He retired in 1989, but he still comes in every week." "How do you spend forty-two years on one species of plant?" I asked. "It's remarkable, isn't it?" Fortey agreed. He thought for a moment. "He's very thorough apparently." The lift door opened to reveal a bricked over opening. Fortey looked confounded. "That's very strange," he said. "That used to be Botany back there." He punched a button for another floor, and we found our way at length to Botany by means of back staircases and discreet trespass through yet more departments where investigators toiled lovingly over once-living objects. ↗
In the statistical gargon used in psychology, p refers to the probability that the difference you see between two groups (of introverts and extroverts, say, or males and females) could have occurred by chance. As a general rule, psychologists report a difference between two groups as 'significant' if the probability that it could have occurred by chance is 1 in 20, or less. The possibility of getting significant results by chance is a problem in any area of research, but it's particularly acute for sex differences research. Supppose, for example, you're a neuroscientist interested in what parts of the brain are involved in mind reading. You get fifteen participants into a scanner and ask them to guess the emotion of people in photographs. Since you have both males and females in your group, you rin a quick check to ensure that the two groups' brains respond in the same way. They do. What do you do next? Most likely, you publish your results without mentioning gender at all in your report (except to note the number of male and female participants). What you don't do is publish your findings with the title "No Sex Differences in Neural Circuitry Involved in Understanding Others' Minds." This is perfectly reasonable. After all, you weren't looking for gender difference and there were only small numbers of each sex in your study. But remember that even if males and females, overall, respond the same way on a task, five percent of studies investigating this question will throw up a "significant" difference between the sexes by chance. As Hines has explained, sex is "easily assessed, routinely evaluated, and not always reported. Because it is more interesting to find a difference than to find no difference, the 19 failures to observe a difference between men and women go unreported, whereas the 1 in 20 finding of a difference is likely to be published." This contributes to the so-called file-drawer phenomenon, whereby studies that do find sex differences get published, but those that don't languish unpublished and unseen in a researcher's file drawer. ↗
I am now completing research supported by NSF and NEH that is mapping changes in the English language through all of North America, for both mainstream and minority communities. ↗
It would be wrong to assume that one must stay with a research programme until it has exhausted all its heuristic power, that one must not introduce a rival programme before everybody agrees that the point of degeneration has probably been reached. ↗
