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What Makes Us Happy?
4 페이지로 이루어진, 아주 긴 글이지만 시간이 남고 여력이 있다면 읽어볼 만 하다. 1937년 Harvard에 입학한 남학생 268명을 대상으로 그 후 72년동안 그들이 지나쳐 온 전쟁, 사회생활, 결혼, 이혼, 가정생활, 노년을 추척한 기록을 바탕으로 한 연구 프로젝트 (프로젝트의 이름은 The Grant Studies)의 결과에 대한 글이다. 사회적으로 성공하다가 마약이나 알콜 중독 등으로 갑자기 인생이 망가져버린 사례들을 제시하면서 '행복의 비밀은 무엇인가' 에 대한 질문을 통계 조사로 결론지었다. 물론 ensemble average는 아니고 time average겠지만. 몇 가지 단락을 옮겨오자면... What allows people to work, and love, as they grow old? (중략) Employing mature adaptations was one. The others were education, stable marriage, not smoking, not abusing alcohol, some exercise, and healthy weight. Of the 106 Harvard men who had five or six of these factors in their favor at age 50, half ended up at 80 as what Vaillant called “happy-well” and only 7.5 percent as “sad-sick.” Meanwhile, of the men who had three or fewer of the health factors at age 50, none ended up “happy-well” at 80. Even if they had been in adequate physical shape at 50, the men who had three or fewer protective factors were three times as likely to be dead at 80 as those with four or more factors. Vaillant’s other main interest is the power of relationships. “It is social aptitude,” he writes, “not intellectual brilliance or parental social class, that leads to successful aging.” Warm connections are necessary—and if not found in a mother or father, they can come from siblings, uncles, friends, mentors. The men’s relationships at age 47, he found, predicted late-life adjustment better than any other variable, except defenses. Good sibling relationships seem especially powerful: 93 percent of the men who were thriving at age 65 had been close to a brother or sister when younger. In an interview in the March 2008 newsletter to the Grant Study subjects, Vaillant was asked, “What have you learned from the Grant Study men?” Vaillant’s response: “That the only thing that really matters in life are your relationships to other people.” “Their lives were too human for science, too beautiful for numbers, too sad for diagnosis and too immortal for bound journals." (중략) Indeed, the lives themselves—dramatic, pathetic, inspiring, exhausting—resonate on a frequency that no data set could tune to.
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