2. 外语
  3. The Happiness Effect [A]The next time you get the flu, there will almost certainly be someone you can blame for your pain. There

The Happiness Effect [A]The next time you get the flu, there will almost certainly be someone you can blame for your pain. There

admin2013-11-11  39
问题                         The Happiness Effect
[A]The next time you get the flu, there will almost certainly be someone you can blame for your pain. There’s the inconsiderate co-worker who decided to drag himself to the office and spent the day sniffling, sneezing and shivering in the cubicle next to yours. Or your child’s best friend, the one who showed up for a playdate with a runny nose and a short supply of tissues. Then there’s the guy at the gym who spent more time sneezing than sweating on the treadmill before you used it.
[B]You’re right to pass the blame. Pathogens(致病菌)like the influenza virus pass like a holiday fruitcake from person to person, but you probably don’t think much past the one who gave it directly to you. An infectious-disease expert, on the other hand, would not be satisfied to stop there. What about the person who passed the virus on to your colleague, the one before him and others earlier still? Contagious(传染性的)diseases operate like a giant infectious network, spreading like the latest YouTube clip among friends of friends online. We’re social animals; we share.
[C]So public-health experts are beginning to wonder whether certain health-related behaviors are just as contagious as microbes. If you’re struggling with your weight, did you in effect catch a case of fat by learning poor eating and exercise habits from a friend or family member who was similarly infected by someone else? If you smoke, do you light up because you were behaviorally contaminated by smokers who convinced you of the coolness of the habit? Even more important, if such unhealthy behaviors are contagious, are healthy ones — like quitting smoking or exercising — equally so? And what if not only behaviors but also moods and mental states work the same way? Can you catch a case of happy?
[D]Increasingly, the answer seems to be yes. That’s the intriguing conclusion from a body of work by Harvard social scientist Dr. Nicholas Christakis and his political-science colleague James Fowler at the University of California at San Diego. The pair created a sensation with their announcement earlier this month of a 20-year study showing that emotions can pass among a network of people up to three degrees of separation away, so your joy may, to a larger extent than you realize, be determined by how cheerful your friends’ friends’ friends are, even if some of the people in this chain are total strangers to you.
[E]If that’s so, it creates a whole new paradigm for the way people get sick and, more important, how to get them healthy. It may mean that an individual’s well-being is the product not just of his behaviors and emotions but more of the way they feed into a larger social network. Think of it as health Facebook-style. "We have a collective identity as a population that transcends individual identity," says Christakis. "This superorganism has an anatomy(解剖学), physiology, structure and function that we are trying to understand."
[F]In their most recent paper, published in the British Medical Journal, Christakis and Fowler explored the emotional state of nearly 5,000 people and the more than 50,000 social ties they shared. At three points during the long study, all the participants answered a standard questionnaire to determine their happiness level, so that the scientists could track changes in emotional state.
[G]That led to their intriguing finding of just how contagious happiness can be: if a subject’s friend was happy, that subject was 15% more likely to be happy too; if that friend’s friend was happy, the original subject was 10% more likely to be so. Even if the subject’s friend’s friend’s friend — entirely unknown to the subject — was happy, the subject still got a 5.6% boost. The happiness chain also worked in the other direction, radiating from the subject out to his friends.
[H]The happiness dividend is more powerful if two people not only know each other but also are equally fond of each other. Happiness is more infectious in mutual relationships(in which both people name the other as a friend)than in unreciprocated ones(in which only one is named).
[I]And it’s not just in sterile(枯燥乏味的)study settings that the contagion of happiness is spreading. Christakis and Fowler noticed that people who are smiling on their Facebook pages tend to cluster together, forming an online social circle like a delirious flock of cyberbirds. And while some of this joy can certainly be traced to the copycat effect — if your friends post smiling pictures, you might feel like a grouch(不高兴的人)if you don’t too — Christakis and Fowler are analyzing the clusters to see if something more infectious might be at work.
[J]Skeptics raise other concerns, ones that go beyond the copycat effect. Couldn’t happy people simply be exposed to similar lifestyles or social factors that explain their shared joy, such as favorable weather, low unemployment rates or a winning baseball team? If that were the case, argue the authors, then happiness would spread more uniformly among all the relationships; instead, it varied depending on whether the friendship was mutual or merely one-sided. As the investigators teased out these factors, they found that environment didn’t have nearly the power that relationships did.
[K]The infectiousness of happiness is only the latest in a series of similar phenomena Christakis and Fowler have stud-ied. In 2007 they published a paper showing that obesity travels across webs in a similar way, with individuals having a 57% greater risk of being overweight if they have an obese friend. The same holds true for quitting smoking, with success 30% more common among friends of quitters than among friends of smokers.
[L]In all these cases, there’s a predictable topography(地形)to how people influence one another, one that can be reduced to a sort of social map. People who are central to their networks — who in effect are the hub through which most of the other relationships or information flows — may have the most influence on others and in turn are the most influenced by them. But just because you start off at the center of your web does not guarantee that you’ll stay there. In the 1970s, smokers were more likely to occupy that focal position in their network of friends and family. Look at a similar social map today, and you’ll see that the smokers have drifted to the periphery(外围).
[M]The better this kind of mapping becomes, the more value it has.
[N]Officials at the Centers for Disease Control and Prevention(CDC)are exploiting the connectedness of youngsters in online social networks, for example, to improve flu-vaccination rates, not just among those under age 18 but among all the people to whom these children have ties. "Because of their social and peer networks, children have a higher likelihood of sharing information with the most people," says Jay Bernhardt of the CDC. By targeting youngsters on these sites with information about the importance of annual flu shots, health officials hope to trigger a literal and figurative viral wave of vaccination among the kids’ peers, their peers’ peers, and even those peers’ parents and grandparents.
[O]"We are always looking for exciting new areas of research that will help people live healthier," says Richard Suzman, director of the division of behavioral and social research at the National Institute on Aging. "Without a doubt, I see this as a very promising area." And with the health community a web like any other, expect that idea to spread further and further.
The happiness dividend can be more powerful when two people who are familiar with each other are also fond of each other.
选项
答案H
解析 根据题干中的The happiness dividend，more powerful以及fond of each other将本题出处定位于[H]段首句。题干中的people who are familiar with each other对应文中的people…know each other。本句意为“在双方既相互了解又互相喜欢的情况下，快乐的收益较高”。
转载请注明原文地址:https://kaotiyun.com/show/ka27777K
0

大学英语六级

相关试题推荐
随机试题
最新回复(0)