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1、2018年考研英语一真题原文及答案解析完整版 2018 年全国硕士研究生入学统一考试英语( 一) Section I Use of English Directions: Read the following text. Choose the best word (s) for each numbered blank and mark A, B, C or D on the ANSWER SHEET. (10 points) Trust is a tricky business. On the one hand, its a necessary condition 1 many worthwh
2、ile things: child care, friendships, etc. On the other hand, putting your 2, in the wrong place often carries a high 3. 4, why do we trust at all? Well, because it feels good. 5 people place their trust in an individual or an institution, their brains release oxytocin, a hormone that 6 pleasurable f
3、eelings and triggers the herding instruct that prompts humans to 7 with one another. Scientists have found that exposure 8 this hormone puts us in a trusting 9: In a Swiss study, researchers sprayed oxytocin into the noses of half the subjects; those subjects were ready to lend significantly higher
4、amounts of money to strangers than were their 10 who inhaled something else. 11 for us, we also have a sixth sense for dishonesty that may 12 us. A Canadian study found that children as young as 14 months can differentiate 13 a credible person and a dishonest one. Sixty toddlers were each 14 to an a
5、dult tester holding a plastic container. The tester would ask, “What s in here? ”before looking into the container, smiling, and exclaiming, “Wow! ” Each subject was then invited to look 15. Half of them found a toy; the other half 16 the container was empty-and realized the tester had 17 them. Amon
6、g the children who had not been tricked, the majority were 18 to cooperate with the tester in learning a new skill, demonstrating that they trusted his leadership. 19, only five of the 30 children paired with the “20 ”tester participated in a follow-up activity. 1. A on B like C for D from 2. A fait
7、h B concern C attention D interest 3. A benefit B debt C hope D price 4. A Therefore B Then C Instead D Again 5. AUntil B Unless C Although D When 6. A selects B produces C applies D maintains 7. A consult B compete C connect D compare 8. A at B by Cof Dto 9. A context B mood C period D circle 10.A
8、counterparts B substitutes C colleagues Dsupporters 11.A Funny B Lucky C Odd D Ironic 12.A monitor B protect C surprise D delight 13.A between B within C toward D over 14.A transferred B added C introduced D entrusted 15.A out B back C around D inside 16.A discovered B proved C insisted D .remembere
9、d 17.A betrayed Bwronged C fooled D mocked 18.A forced B willing C hesitant D entitled 19.A In contrast B As a result C On the whole D For instance 20.A inflexible B incapable C unreliable D unsuitable Part A Directions: Section II Reading Comprehension Read the following four texts. Answer the ques
10、tions below each text by choosing A, B, C or D. Mark your answers on the ANSWER SHEET. (40 points) Text 1 Among the annoying challenges facing the middle class is one that will probably go unmentioned in the next presidential campaign: What happens when the robots come for their jobs? Dont dismiss t
11、hat possibility entirely. About half of U.S. jobs are at high risk of being automated, according to a University of Oxford study, with the middle class disproportionately squeezed. Lower-income jobs like gardening or day care dont appeal to robots. But many middle-class occupations-trucking, financi
12、al advice, software engineering have aroused their interest, or soon will. The rich own the robots, so they will be fine. This isnt to be alarmist. Optimists point out that technological upheaval has benefited workers in the past. The Industrial Revolution didnt go so well for Luddites whose jobs we
13、re displaced by mechanized looms, but it eventually raised living standards and created more jobs than it destroyed. Likewise, automation should eventually boost productivity, stimulate demand by driving down prices, and free workers from hard, boring work. But in the medium term, middle-class worke
14、rs may need a lot of help adjusting. The first step, as Erik Brynjolfsson and Andrew McAfee argue in The Second Machine Age, should be rethinking education and job training. Curriculums from grammar school to college- should evolve to focus less on memorizing facts and more on creativity and complex
15、 communication. Vocational schools should do a better job of fostering problem-solving skills and helping students work alongside robots. Online education can supplement the traditional kind. It could make extra training and instruction affordable. Professionals trying to acquire new skills will be
16、able to do so without going into debt. The challenge of coping with automation underlines the need for the U.S. to revive its fading business dynamism: Starting new companies must be made easier. In previous eras of drastic technological change, entrepreneurs smoothed the transition by dreaming up w
17、ays to combine labor and machines. The best uses of 3D printers and virtual reality havent been invented yet. The U.S. needs the new companies that will invent them. Finally, because automation threatens to widen the gap between capital income and labor income, taxes and the safety net will have to
18、be rethought. Taxes on low-wage labor need to be cut, and wage subsidies such as the earned income tax credit should be expanded: This would boost incomes, encourage work, reward companies for job creation, and reduce inequality. Technology will improve society in ways big and small over the next fe
19、w years, yet this will be little comfort to those who find their lives and careers upended by automation. Destroying the machines that are coming for our jobs would be nuts. But policies to help workers adapt will be indispensable. 21.Who will be most threatened by automation? A Leading politicians.
20、 BLow-wage laborers. CRobot owners. DMiddle-class workers. 22 .Which of the following best represent the authors view? A Worries about automation are in fact groundless. BOptimists opinions on new tech find little support. CIssues arising from automation need to be tackled DNegative consequences of
21、new tech can be avoided 23.Education in the age of automation should put more emphasis on A creative potential. Bjob-hunting skills. Cindividual needs. Dcooperative spirit. 24.The author suggests that tax policies be aimed at A encouraging the development of automation. Bincreasing the return on cap
22、ital investment. Ceasing the hostility between rich and poor. Dpreventing the income gap from widening. 25.In this text, the author presents a problem with A opposing views on it. Bpossible solutions to it. Cits alarming impacts. Dits major variations. Text 2 A new survey by Harvard University finds
23、 more than two-thirds of young Americans disapprove of President Trump s use of Twitter. The implication is that Millennials prefer news from the White House to be filtered through other source, Not a presidents social media platform. Most Americans rely on social media to check daily headlines. Yet
24、 as distrust has risen toward all media, people may be starting to beef up their media literacy skills. Such a trend is badly needed. During the 2016 presidential campaign, nearly a quarter of web content shared by Twitter users in the politically critical state of Michigan was fake news, according
25、to the University of Oxford. And a survey conducted for BuzzFeed News found 44 percent of Facebook users rarely or never trust news from the media giant. Young people who are digital natives are indeed becoming more skillful at separating fact from fiction in cyberspace. A Knight Foundation focus-gr
26、oup survey of young people between ages 14and24 found they use “distributed trust ”to verify stories. They cross-check sources and prefer news from different perspectives especially those that are open about any bias. “Many young people assume a great deal of personal responsibility for educating th
27、emselves and actively seeking out opposing viewpoints,”the survey concluded. Such active research can have another effect. A 2014 survey conducted in Australia, Britain, and the United States by the University of Wisconsin-Madison found that young peoples reliance on social media led to greater poli
28、tical engagement. Social media allows users to experience news events more intimately and immediately while also permitting them to re-share news as a projection of their values and interests. This forces users to be more conscious of their role in passing along information. A survey by Barna resear
29、ch group found the top reason given by Americans for the fake news phenomenon is “reader error, ”more so than made-up stories or factual mistakes in reporting. About a third say the problem of fake news lies in “misinterpretation or exaggeration of actual news ”via social media. In other words, the
30、choice to share news on social media may be the heart of the issue. “This indicates there is a real personal responsibility in counteracting this problem, ”says Roxanne Stone, editor in chief at Barna Group. So when young people are critical of an over-tweeting president, they reveal a mental discip
31、line in thinking skills and in their choices on when to share on social media. 26. According to the Paragraphs 1 and 2, many young Americans cast doubts on A the justification of the news-filtering practice. B people s preference for social media platforms. C the administrations ability to handle in
32、formation. D social media was a reliable source of news. 27. The phrase “beer up ”(Line 2, Para. 2) is closest in meaning to A sharpen B define C boast D share 28. According to the knight foundation survey, young people A tend to voice their opinions in cyberspace. B verify news by referring to dive
33、rse resources. C have s strong sense of responsibility. D like to exchange views on “distributed trust ” 29. The Barna survey found that a main cause for the fake news problem is A readers outdated values. B journalists biased reporting C readers misinterpretation D journalists made-up stories. 30.
34、Which of the following would be the best title for the text? A A Rise in Critical Skills for Sharing News Online B A Counteraction Against the Over-tweeting Trend C The Accumulation of Mutual Trust on Social Media. D The Platforms for Projection of Personal Interests. Text 3 Any fair-minded assessme
35、nt of the dangers of the deal between Britains National Health Service (NHS) and DeepMind must start by acknowledging that both sides mean well. DeepMind is one of the leading artificial intelligence (AI) companies in the world. The potential of this work applied to healthcare is very great, but it
36、could also lead to further concentration of power in the tech giants. It Is against that background that the information commissioner, Elizabeth Denham, has issued her damning verdict against the Royal Free hospital trust under the NHS, which handed over to DeepMind the records of 1.6 million patien
37、ts In 2015 on the basis of a vague agreement which took far too little account of the patients rights and their expectations of privacy. DeepMind has almost apologized. The NHS trust has mended its ways. Further arrangements- and there may be many-between the NHS and DeepMind will be carefully scrut
38、inised to ensure that all necessary permissions have been asked of patients and all unnecessary data has been cleaned. There are lessons about informed patient consent to learn. But privacy is not the only angle in this case and not even the most important. Ms Denham chose to concentrate the blame o
39、n the NHS trust, since under existing law it “controlled ”the data and DeepMind merely “processed it. But this distinction misses the point that it is processing and aggregation, not the mere possession of bits, that gives the data value. The great question is who should benefit from the analysis of
40、 all the data that our lives now generate. Privacy law builds on the concept of damage to an individual from identifiable knowledge about them. That misses the way the surveillance economy works. The data of an individual there gains its value only when it is compared with the data of countless mill
41、ions more. The use of privacy law to curb the tech giants in this instance feels slightly maladapted. This practice does not address the real worry. It is not enough to say that the algorithms DeepMind develops will benefit patients and save lives. What matters is that they will belong to a private monopoly which developed them using public resources. If software promises to save lives on the scale that dugs now can, big data may be expected to behave as a big pharm has done. We are still at the beginning of this revolut