Jack coughed slightly and offered his hand. “Hi, uh. I’m Jack.”Kim took it. “Jack what?”“Huh?”“Your last name, silly.”“Jackson.”She blinked at him. “Your name is Jack Jackson?”He blushed. “No, uh, my first name’s Rhett, but I hate it, so…” He gestured to the chair and she sat. Her dress rode up several inches, exposing pleasing long lines of creamy skin. “Well, Jack, what’s your field of study?”“Biological Engineering, Genetics, and Microbiology. Post-doc. I’m working on a research project at the institute.”“Really? Oh, uh, my apple martini’s getting a little low.”“I’ve got that, one second.” He scurried to the bar and bought her a fresh one. She sipped and managed to make it look not only seductive but graceful as well. “What do you want to do after you’re done with the project?” Kim continued.“Depends on what I find.”She sent him a simmering smile. “What are you looking for?” Immediately, Jack’s eyes lit up and his posture straightened. “I started the project with the intention of learning how to increase the reproduction of certain endangered species. I had interest in the idea of cloning, but it proved too difficult based on the research I compiled, so I went into animal genetics and cellular biology. It turns out the animals with the best potential to combine genes were reptiles because their ability to lay eggs was a smoother transition into combining the cells to create a new species, or one with a similar ancestry that could hopefully lead to rebuilding extinct animals via surrogate birth or in-vitro fertilization. We’re on the edge of breaking that code, and if we do, it would mean that we could engineer all kinds of life and reverse what damage we’ve done to the planet’s ecosystem.”Kim stared. “Right. Would you excuse me for a second?”She wiggled off back to her pack of friends by the bar. Judging by the sniggering and the disgusted glances he was getting, she wasn’t coming back. Jack sighed and finished off his beer, massaging his forehead. “Yes, brilliant move. You blinded her with science. Genius, Jack.”He ordered a second one and finished it before he felt smallish hands on his shoulders and a pair of soft lips on his cheek. He turned to find Kamala had returned, her smile unnaturally bright in the black lights glowing over the room. “So…how did it go with Kim?”He shot her a flat look. “You notice the chair is empty.”Kamala groaned. “You talked about the research project, didn’t you?”“No!” She glared at him.“…maybe…”“You’re so useless, Jack.” She paused and then tousled his hair a bit. “Cheer up. The night’s still young. I’m not giving up on you.”He smiled in spite of himself. “Yet.”Her brown eyes flashed. “Never.
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.