题目内容
162. At the social gathering the weather is the subject which usually breaks the _____.
A.ice |
B.iceberg |
C.topic |
D.Instance |
A
【解析】略
A. offers B. influences C. uncovered D. exactly E. big F. found G. campaigns H. involved J. properly I. notion |
What’s in a name? Letters offer clues to one’s future decisions, apparently. Previous studies have suggested that maybe a person’s monogram __1__ his life choices — where he works, whom he marries or where he lives — because of “implied self-esteem (自负),” or the temptation of positive self-associations. For instance, a person named Fred might be attracted to the __2__ of living in Fresno, working for Forever 21 or driving a Ford F-150.
Now a new study by professor Uri takes another look at the so-called name-letter effect and __3__ other explanations for the phenomenon. He analyzed records of political donations in the U.S. during the 2004 campaign — which included donors’ names and employers — and found that the name of a person’s workplace more closely related to the first three letters of a person’s name than with just the first letter. But he suggests that the reason for the association isn’t implied self-esteem, but perhaps something __4__ the opposite.
Duyck, one of the researchers whose previous work __5__ the name-letter effect, isn’t so quick to abandon the implied self-esteem theory. He pointed out that the sample group Uri studied may have biased the results: Uri analyzed the name-letter effect in a sample of people who donated money to political __6__. Still, Duyck notes that Uri’s theories are credible, and that even while some people may __7__ the same name of companies, employees may be tending to those companies because they start with the same letter as their names. In the end, whatever the explanation for the name-letter effect, no one really disputes that self-esteem is __8__ on some level. But the true importance of the effect is up for debate. “I can’t imagine people don’t like their own letter more than other letters,” says Uri, “but the differences it makes in really __9__ decisions are probably slim.”