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Blink_ The Power of Thinking Without Thinking - Malcolm Gladwell [7]

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mounted on raised platforms. They both had electrodes and sensors clipped to their fingers and ears, which measured things like their heart rate, how much they were sweating, and the temperature of their skin. Under their chairs, a “jiggle-o-meter” on the platform measured how much each of them moved around. Two video cameras, one aimed at each person, recorded everything they said and did. For fifteen minutes, they were left alone with the cameras rolling, with instructions to discuss any topic from their marriage that had become a point of contention. For Bill and Sue it was their dog. They lived in a small apartment and had just gotten a very large puppy. Bill didn’t like the dog; Sue did. For fifteen minutes, they discussed what they ought to do about it.

The videotape of Bill and Sue’s discussion seems, at least at first, to be a random sample of a very ordinary kind of conversation that couples have all the time. No one gets angry. There are no scenes, no breakdowns, no epiphanies. “I’m just not a dog person” is how Bill starts things off, in a perfectly reasonable tone of voice. He complains a little bit — but about the dog, not about Susan. She complains, too, but there are also moments when they simply forget that they are supposed to be arguing. When the subject of whether the dog smells comes up, for example, Bill and Sue banter back and forth happily, both with a half smile on their lips.

Sue: Sweetie! She’s not smelly…

Bill: Did you smell her today?

Sue: I smelled her. She smelled good. I petted her, and my hands didn’t stink or feel oily. Your hands have never smelled oily.

Bill: Yes, sir.

Sue: I’ve never let my dog get oily.

Bill: Yes, sir. She’s a dog.

Sue: My dog has never gotten oily. You’d better be careful.

Bill: No, you’d better be careful.

Sue: No, you’d better be careful…. Don’t call my dog oily, boy.

1. The Love Lab

How much do you think can be learned about Sue and Bill’s marriage by watching that fifteen-minute videotape? Can we tell if their relationship is healthy or unhealthy? I suspect that most of us would say that Bill and Sue’s dog talk doesn’t tell us much. It’s much too short. Marriages are buffeted by more important things, like money and sex and children and jobs and in-laws, in constantly changing combinations. Sometimes couples are very happy together. Some days they fight. Sometimes they feel as though they could almost kill each other, but then they go on vacation and come back sounding like newlyweds. In order to “know” a couple, we feel as though we have to observe them over many weeks and months and see them in every state — happy, tired, angry, irritated, delighted, having a nervous breakdown, and so on — and not just in the relaxed and chatty mode that Bill and Sue seemed to be in. To make an accurate prediction about something as serious as the future of a marriage — indeed, to make a prediction of any sort — it seems that we would have to gather a lot of information and in as many different contexts as possible.

But John Gottman has proven that we don’t have to do that at all. Since the 1980s, Gottman has brought more than three thousand married couples — just like Bill and Sue — into that small room in his “love lab” near the University of Washington campus. Each couple has been videotaped, and the results have been analyzed according to something Gottman dubbed SPAFF (for specific affect), a coding system that has twenty separate categories corresponding to every conceivable emotion that a married couple might express during a conversation. Disgust, for example, is 1, contempt is 2, anger is 7, defensiveness is 10, whining is 11, sadness is 12, stonewalling is 13, neutral is 14, and so on. Gottman has taught his staff how to read every emotional nuance in people’s facial expressions and how to interpret seemingly ambiguous bits of dialogue. When they watch a marriage videotape, they assign a SPAFF code to every second of the couple’s interaction, so that a fifteen-minute conflict discussion ends up being translated into a row of eighteen hundred numbers

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