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An epidemic is the occurrence of a disease which affects a very large number of people living in an area and which spreads quickly to other people. Like infectious diseases, ideas in the academic world are spreadable. But why some travel far and wide while equally good ones remain in relative insignificance has been a mystery. Now a team of computer scientists has used an epidemiological model to imitate how ideas move from one academic institution to another. The model showed that ideas originating at famous institutions caused bigger “epidemics” than equally good ideas from less well-known places, explains Allison Morgan, a computer scientist at the University of Colorado Boulder and lead author of the new study. “This implies that where an idea is born shapes how far it spreads, holding the quality of the idea constant.” says senior author Aaron Clauset, also at Boulder.

Not only is this unfair --- “it reveals a big weakness in how we’re doing science,” says Simon DeDeo, a professor of social and decision sciences at Carnegie Mellon University, who was not involved in the study. There are many highly trained people with good ideas who do not end up at top institutions. “They are producing good ideas, and we know those ideas are getting lost,” DeDeo says. “Our science, our scholarship, is not as good because of this.”

The Colorado researchers analyzed an existing data set of computer science department hires in North America, as well as a database of publications by these hires. First they looked at how five big ideas in computer science spread to new institutions. They found that hiring a new member accounted for a little more than a third of the time --- and in 81 percent of those cases, transfers took place from higher- to lower-status universities. Then the team imitated the broadcasting of ideas using an infectious disease model and found that the size of an idea “epidemic” (as measured by the number of institutions that published studies on an idea after it originated) depended on the status of the originating institution. The findings were published online last October in EPJ Data Science.

The researchers’ model suggests that there “may be a number of quite good ideas that originate in the middle of the pack, in terms of universities,” Clauset says. DeDeo agrees. There is a lot of good work coming out of less famous places, he says: “You can learn a huge amount from it, and you can learn things that other people don’t know because they’re not even paying attention.”

1.The underlined word “this” in paragraph 2 refers to the fact that _________.

A.good ideas from less important institutions lack influence.

B.the quality of the original ideas tends to be not easy to maintain.

C.scholars in insignificant institutions consider their ideas valueless.

D.the time when good ideas were born decides how far they may spread.

2.The case of some hires in paragraph 3 is used to indicate _________.

A.why the originating institutions transfer their new findings.

B.the way the movements of some new ideas happen and their effects.

C.how they carry the ideas from lower - to higher - status institutions.

D.the statistics the epidemological model provides for the researchers.

3.Researchers such as Clauset are very much concerned about _________.

A.losing quite a number of great and creative thoughts.

B.missing the opportunities of getting more well-known.

C.misusing the epidemiological model in scientific research areas.

D.having difficulty in finding more proper science department hires.

4.Which of the following might be the best title of the passage?

A.Infectious Diseases. B.Original Ideas.

C.Epidemiological Model. D.Idea Epidemic.

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