《考研《英语一》岳阳市君山区2023年高分冲刺试题含解析》由会员分享，可在线阅读，更多相关《考研《英语一》岳阳市君山区2023年高分冲刺试题含解析（13页珍藏版）》请在金锄头文库上搜索。
1、考研英语一岳阳市君山区2023年高分冲刺试题Section I Use of EnglishDirections: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)About a month ago, while in the drive through at Starbucks, I noticed a woman in a car behind me who appeared to be
2、having a bad day. There were two kids in the back who seemed to have too much at 8 am on a Sunday morning, because they were shouting loudly. The moved slowly and at one point while I was pulling the car forward, the sad woman behind me my car. I could tell this her. The entire time that I waited in
3、 line for my coffee this woman didnt . Looking back at her I could tell she was wondering “Why me? Why today?” When I up and paid for my coffee I requested that the barista(咖啡吧员) of Starbucks give the woman behind me a smile card and paid for her coffee. Just 30 minutes later I was again in line at
4、Starbucks. I heard a slam of a car door but thought nothing of it. I was when the same woman came up to my drivers side window. She me a twenty-dollar bill and the same smile card I had given to her. She smiled and said, “These are for you. You are the one who gave these to me , right? All I need yo
5、u to do is ask the barista to give the back to me.” It was amazing! It was as if this woman had been waiting to show her for what I had done! When she got back into her today she was all smiles. I could tell she had the same feeling as I had on that early Sunday morning. It was nice to have my coffe
6、e paid for, but what made me feel even better was seeing the happiness and smile on her face. As I pulled out of the drive-thru, she waved and yelled out, “Have a day!” I yelled back “You too!” and waved her goodbye.1、AforceBstrengthCpowerDenergy2、AlineBtimeCsunDbus3、AknockedBtouchedCkicked Dwatched
7、4、AexcitedBcalmedCworriedDentertained5、Aapologize Bsmile CcomplainDbother6、ApulledBlooked CturnedDwalked7、AstandingBwaitingCparkingDpacing8、AamusedBconfusedCdisappointedDshocked9、AhandedBowedCpresentedDasked10、AcleverBkindChonest Dmodest11、Aprivately BsecretlyCoriginallyDtotally12、AcardBchange Cbill
8、Dcoffee13、Aconsideration BrespectCdesireDappreciation14、AofficeBhomeCcarDroom15、AfreeBquietCregular DgoodSection II Reading ComprehensionPart ADirections:Read the following four texts. Answer the questions below each text by choosing A, B, C or D. Mark your answers on the ANSWER SHEET. (40 points)Te
9、xt 1That robots, automation, and software can replace people might seem obvious to anyone whos worked in automotive manufacturing. But MIT business scholars Erik Brynjolfsson and Andrew McAfees claim is more troubling and controversial. They believe that rapid technological change has been destroyin
10、g jobs faster than it is creating them.They believe that technology increases productivity and makes societies wealthier, but it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers. Technolo
11、gies like the Web, artificial intelligence, and big data are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared.As evidence, Brynjolfsson and McAfee point to a chart on which separate lines represent produ
12、ctivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. Then, beginning in 2000, the lines diverge; productivity continues to rise steadily, but employment suddenly s
13、hrinks. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation.United States Productivity and EmploymentBut are these new technologies really responsible for a decade of lackluster (无生气) job growth? David Autor, an economist at MIT
14、 who has studied the connections between jobs and technology, doubts that technology could account for such a sudden change in total employment. Moreover, he also doubts that productivity has, in fact, risen steadily in the United States in the past decade. If hes right, it raises the possibility th
15、at poor job growth could be simply a result of a depressed economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but theres not a lot of evidence that its linked to computers.” “To be sure, computer technologies are changing the types of jobs available, but that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”Lawrence Katz, a Harvard economist, says that while technological changes can be
