2020高考英语三模前阅读理解专题练05(学生版)三年真题研读专练.pdf
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1、三模前阅读理解专题练05题组一AHistorian Tom Holland is the award-winning author of Rubicon,Persian Fire and Millennium.He appears regularlyon radio,TV and in print.His latest book Dynasty is published in paperback by Abacus.Moominsummer Madness By Tove JansoonWhat I love about this book,as a child and still today
2、,is its mix of the fantastical and normal.On the one hand,ifs about a family and their friends all enjoying themselves,quite happy not doing much.On the other hand,its aboutcharacters that can change into odd shapes,magicianscoming down from the moon and peculiar creaturesemerging from the roof.That
3、 mix of the familiar and theextraordinary informs all my writing.T T H R O O C r r u ST H H H ltT lO R IH SThe Histories By HerodoTusBy the time I was 12,1 was obsessed by AncientGreece and Rome.At first,I found the early section of TheHistories a real grind because its like a long shaggy dogIn the
4、second half I was rewarded with the stories Idbeen waiting for,like the battles of Marathon,Salamis and Thermopylae.Over the years,I come tovalue the infectious curiosity of the first half and theportrait of the world in the fifth century BC seenthrough the eyes of this extraordinary Greekhistorian.
5、A Distant Mirror By BarBara W TucHmanTuchmans book The Guns of August won thePulitzer Prize,but its this slightly less well-knownwork that provided me with a role model for my ownwriting.Both scholarly and interesting,its a portraitof the 14th century in Western Europe and vividlyevokes medieval civ
6、ilization buffeted by cataclysms:the Black Death,the Peasants?Revolt and the GreatPapal Schism.I felt I knew what it was to die of theplague or to have a sword put through me real56.Tom Holland now finds the first half of The Hi s t o r i e s.story that never gets to the point.stories told remarkabl
7、yA.off the point B.culture-centered C.really boring D.quite entertaining57.Which book does Tom Holland appreciate and try to copy its style?A.The HistoriesB.A Distant Mirror C.The Guns of August D.Moominsummer MadnessBIn Weapons of Math Destruction,data scientist Cathy ONeil explains how big data ex
8、ists everywhere in ourlives,and that we hardly even notice it until it affects us directly.One application that has become particularlycommon is the use of algorithms(算法)to evaluate job performance.She tells the story of Sarah Wysocki,a teacher who,despite being widely respected by her students,thei
9、rparents and her colleagues,was fired because she performed poorly according to an algorithm.When an algorithmrates you poorly,you are immediately branded as an underperformer and there is rarely an opportunity to appealagainst those judgments.In many cases,methods are considered secrets and no deta
10、ils are shared.And data oftenseems convincing.As a matter of fact,the belief that school performance in America is declining is based on a data mistake.ANation at Risk is the report that rang the initial alarm bells about declining SAT(Scholastic Assessment Test)scores.Yet if they had taken a closer
11、 look,they would have noticed that the scores in each smaller group were increasing.The reason for the decline in the average score was that more disadvantaged kids were taking the test.However,due to the data mistake,teachers as a whole were judged to be failing.Wall Street is famous for its mathem
12、aticians who build complex models to predict market movements anddevelop business plans.These are really smart people.Even so,it is not at all uncommon for their models to fail.The key difference between those models and many of the ones being used these days is that Wall Street traderslose money wh
13、en their data models go wrong.However,as ONeil points out in her book,the effects ofwidely-used machine-driven judgments are often not borne by those who design the algorithms,but by everyoneelse.As we increasingly rely on machines to make decisions,we need to ask these questions:What assumptions ar
14、ethere in your model?What hasnt been taken into account?How are we going to test the effectiveness of theconclusions?Clearly,something has gone terribly wrong.When machines replace humans to make a judgment,weshould hold them to a high standard.We should know how the data was collected.And when numb
15、ers lie,weshould stop listening to them.58.What does the example of Sarah Wysocki mainly show?A.The drawback of big data.B.The popularity of big data.C.The new challenge teachers face.D.The misunderstanding about algorithms.59.Widely-used machine-driven j u d g m e n t s.A.never make any economic lo
16、ssB.can lead to many innocent victimsC.are more complicated than Wall Streets data modelsD.can go wrong more easily than Wall Street9s data models60.What does the author suggest in the last paragraph?A.Making decisions without machines.B.Making sure that the data are reliable.C.Making the algorithms
17、 more effective.D.Making the data and algorithms public.CRonald Reagan ever said,Its true hard work never killed anybody,but I figure,why take the chance?Tosome extent,extra effort seems to be self-defeating.Studies suggest that,after 50 hours a week,employeeproductivity falls sharply.But that doesn
18、t stop some managers from demanding that workers stay chained to their desk for long periods.Jack Ma,the founder of Alibaba,recently praised the 996”model,where employees work from 9 a.m.to 9 p.m.,6days a week,as a huge blessing,.Apparently,presenteeism(Hi 勤主义)is the curse of the modem office worker
19、.There will be days when you do not have much to do:perhaps because you are waiting for someone else in adifferent department,or a different company,to respond to a request.As the clock ticks past 5 pm,there may be nopurpose in staying at your desk.But you can see your boss hard at work and,more imp
20、ortantly,they can see you.So you make an effort to look busy.Some of this may be a self-continuing cycle.If bosses do not like to go home before their employees,andemployees fear leaving before their bosses,everyone is trapped.Staff may feel that they will not get a pay rise,or apromotion,if they ar
21、e not seen to be putting in maximum effort.This is easily confused with long hours.Managers,who are often no good at judging employees*performance,use time in the office as a measure.The consequence isoften wasted effort.We pretend to work and managers pretend to believe us.Rather than work hard,you
22、 try tomake bosses think that you are.Leaving a jacket on your office chair,walking around purposefully with a notebookand sending out emails at odd hours are three of the best-known tricks.After a while this can result in collectiveself-delusion that this pretence is actual work.But presenteeism ha
23、s more serious consequences.It is perhaps most common in Japan,where people attendthe office even when they are in discomfort.In doing so,they are doing neither themselves nor their employers anyfavours.As well as reducing productivity,this can increase medical expenses for the employer.According to
24、 astudy in the Journal of Occupation and Environmental Medicine,these costs can be six times higher for employersthan the costs of absenteeism among workers.Those workers were more likely to experience greater pain and tosuffer from depression.In the evolution of humanity,presenteeism is a recent ph
25、enomenon.In the industrial era,workers were paidnot for their output but for their time,and were required to clock in and out.But modern machinery likesmartphones and laptops is portable.Turning an office into a prison,with prisoners allowed home for the evenings,does nothing for the creativity that
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