1 . On March 7, 1907, the English statistician Francis Galton published a paper which illustrated what has come to be known as the “wisdom of crowds” effect. The experiment of estimation he conducted showed that in some cases, the average of a large number of independent estimates could be quite accurate.
This effect capitalizes on the fact that when people make errors, those errors aren’t always the same. Some people will tend to overestimate, and some to underestimate. When enough of these errors are averaged together, they cancel each other out, resulting in a more accurate estimate. If people are similar and tend to make the same errors, then their errors won’t cancel each other out. In more technical terms, the wisdom of crowds requires that people’s estimates be independent. If for whatever reasons, people’s errors become correlated or dependent, the accuracy of the estimate will go down.
But a new study led by Joaquin Navajas offered an interesting twist (转折) on this classic phenomenon. The key finding of the study was that when crowds were further divided into smaller groups that were allowed to have a discussion, the averages from these groups were more accurate than those from an equal number of independent individuals. For instance, the average obtained from the estimates of four discussion groups of five was significantly more accurate than the average obtained from 20 independent individuals.
In a follow-up study with 100 university students, the researchers tried to get a better sense of what the group members actually did in their discussion. Did they tend to go with those most confident about their estimates? Did they follow those least willing to change their minds? This happened some of the time, but it wasn’t the dominant response. Most frequently, the groups reported that they “shared arguments and reasoned together”. Somehow, these arguments and reasoning resulted in a global reduction in error. Although the studies led by Navajas have limitations and many questions remain, the potential implications for group discussion and decision-making are enormous.
1. What is paragraph 2 of the text mainly about?A.The methods of estimation. | B.The underlying logic of the effect. |
C.The causes of people’s errors. | D.The design of Galton’s experiment. |
A.the crowds were relatively small | B.there were occasional underestimates |
C.individuals did not communicate | D.estimates were not fully independent |
A.The size of the groups. | B.The dominant members. |
C.The discussion process. | D.The individual estimates. |
A.Unclear. | B.Dismissive. | C.Doubtful. | D.Approving. |
Stop Asian Hate
During the course of the COVID-19 pandemic, New York City saw a sharp increase in harassment and violence against Asian people and communities, especially Asian elders. Discrimination on the basis of race, national origin, age, and disability, including having or
We all want to live in a world that is free from prejudice and
Since the pandemic, something has been made nasty in the media by comments from Donald Trump calling it “the China virus”, and ESEA people all over the world have found that their lives have been turned upside down. In the wake of the tragic deaths in the US and several studies
Working towards a world where no racism exists is always important to us, and will always be something
3 . Now that we have briefly explored the history of the short story and heard from a few of its creators, let us consider the role of the reader. Readers are not empty vessels that wait,
My students always
A short story,
Now it is your turn. Form a partnership with your author. During your
During this adventure, I hope you will feel the same as the listeners that surround the neck of my Pueblo storyteller.
1.A.hands | B.sails | C.flags | D.lids |
A.considerations | B.explorations | C.associations | D.interpretations |
A.imagination | B.eagerness | C.determination | D.affection |
A.begged | B.supported | C.encouraged | D.challenged |
A.dealt | B.struggled | C.fought | D.engaged |
A.external | B.artificial | C.classical | D.traditional |
A.ensured | B.analyzed | C.revealed | D.delivered |
A.however | B.furthermore | C.therefore | D.besides |
A.interpret | B.anticipate | C.predict | D.tell |
A.conclusion | B.evaluation | C.summary | D.appreciation |
A.craftsmanship | B.intentions | C.depth | D.character |
A.by itself | B.in vain | C.in question | D.as a whole |
A.observation | B.involvement | C.experiment | D.adventure |
A.journey | B.process | C.dialogue | D.contact |
A.recall | B.confirm | C.identify | D.cancel |
A road trip
Out of all possible road trips, the best one is by car. You finish packing, put everything inside the car, sit inside it, buckle up, look at your friend
I love to meet the sun while driving a road trip in a car.
Spring and autumn are two seasons of the year that are perfect for a road trip. In my opinion, spring is the most inspiring time of the year,
A road trip in autumn is beautiful, too. The golden brush touches
A road trip for me is the moment of communication with nature. It is a dialogue
5 . Thanks to in-depth reporting by the Wall Street Journal, we now know that Facebook has long been aware its product Instagram has harmful effects on the mental health of many adolescent users. Young girls, in particular, struggle with their body image thanks to a constant stream of photos and videos showing beautiful bodies that users don’t think they can attain.
While the information the Journal covered is essential and instructive, it does not tell the whole story. Deep down, this is not an Instagram problem; it’s a people problem. Understanding that distinction can make the difference between a failed attempt to contain a teen’s interest in an addictive app and successfully addressing the underlying problem leading to mental distress induced (诱发) by Instagram.
Critics were quick to shame Facebook for sitting on the data and not releasing it to researchers or academics who asked for it. Others criticize the social media giant for not using the research to create a safer experience for its teen users. The anger, while understandable, is misplaced.
While I’m reluctant to defend Facebook, I’m not sure it’s reasonable to blame the company for withholding data that would hurt its business. Have you ever binge-watched (狂看) a Netflix series? I assure you it wasn’t a healthy endeavor. You were in active, likely did nothing productive, mindlessly snacked and didn’t go outside for fresh air. It is an objectively harmful use of time to stare at a TV or laptop for a full weekend. Should we respond by shaming Netflix for not alerting us to how damaging an addictive product can be?
While it’s reasonable to say Instagram makes esteem issues worse, it strains credulity (夸张到难以置信) to believe it causes them in the first place. You create your own experiences on social media. For the most part, you choose which accounts to follow and engage. If you’re already vulnerable to insecurities and self-sabotage (自损) — as many teens are — you will find accounts to obsess over. And this isn’t a new phenomenon.
Before social media, there were similar issues fueling self-esteem issues. Whether the target be magazines, movies or television shows depicting difficult-to-attain bodies, there has been a relatively steady chorus (异口同声) of experts nothing the damage new media could cause young viewers.
Self-esteem issues have an underlying cause — one that’s independent of social media use. Instagram merely enhances those feelings because it provides infinitely more access to triggers than older forms of media. It’s more worthwhile to address those underlying factors rather than to attack Facebook.
1. The author thinks the criticisms against Instagram __________.A.are successful attempts to change teens’ interest in addictive apps |
B.address the Instagram - induced mental pain |
C.are only based on the data released by Facebook |
D.are not directed at the fundamental problem |
A.compare the criticisms against it and Facebook |
B.defend why Facebook is to blame |
C.suggest the critics’ remarks are not to point |
D.show Netflix does more harm to teens |
A.it is human nature to get addicted to social media |
B.users decide on their experiences on social media |
C.people have a tendency to feel insecure online |
D.people are keen on fabricating their self - profile |
A.the unprecedented criticism facing Facebook |
B.the alarming online habits of teenagers worldwide |
C.the root cause of Instagram - induced mental strains |
D.the harmful impact of Instagram on teenagers |
A.is not distributed, is to be found | B.are not distributed, are to be found |
C.is not distributed, has been found | D.are not distributed, have been found |
7 . We may think we're a culture that gets rid of our worn technology at the first sight of something shiny and new, but a new study shows that we keep using our old devices(装置) well after they go out of style. That’s bad news for the environment — and our wallets — as these outdated devices consume much more energy than the newer ones that do the same things.
To figure out how much power these devices are using, Callie Babbitt and her colleagues at the Rochester Institute of Technology in New York tracked the environmental costs for each product throughout its life — from when its minerals are mined to when we stop using the device. This method provided a readout for how home energy use has evolved since the early 1990s. Devices were grouped by generation — Desktop computers, basic mobile phones, and box-set TVs defined 1992. Digital cameras arrived on the scene in 1997. And MP3 players, smart phones, and LCD TVs entered homes in 2002, before tablets and e-readers showed up in 2007.
As we accumulated more devices, however, we didn't throw out our old ones. "The living-room television is replaced and gets planted in the kids' room, and suddenly one day, you have a TV in every room of the house," said one researcher. The average number of electronic devices rose from four per household in 1992 to 13 in 2007. We're not just keeping these old devices — we continue to use them. According to the analysis of Babbitt's team, old desktop monitors and box TVs with cathode ray tubes are the worst devices with their energy consumption and contribution to greenhouse gas emissions(排放)more than doubling during the 1992 to 2007 window.
So what's the solution(解决方案)? The team's data only went up to 2007, but the researchers also explored what would happen if consumers replaced old products with new electronics that serve more than one function, such as a tablet for word processing and TV viewing. They found that more on-demand entertainment viewing on tablets instead of TVs and desktop computers could cut energy consumption by 44%.
1. What does the author think of new devices?A.They are environment-friendly. | B.They are no better than the old. |
C.They cost more to use at home. | D.They go out of style quickly. |
A.To reduce the cost of minerals. |
B.To test the life cycle of a product. |
C.To update consumers on new technology. |
D.To find out electricity consumption of the devices. |
A.The box-set TV. | B.The tablet. |
C.The LCD TV. | D.The desktop computer. |
A.Stop using them. | B.Take them apart. |
C.Upgrade them. | D.Recycle them. |
8 . One of the curious things about social networks is the way that some messages, pictures, or ideas can spread like wildfire while others that seem just as catchy or interesting barely register at all.
Before you go deep into the puzzle, consider this: If you measure the height of your male friends, for example, the average is about 170 centimeters. You are 172 and your friends are all about the same height as you are. Indeed, the mathematical concept of “average” is a good way to capture the nature of this data set.
But imagine that one of your friends was much taller than you. This person would dramatically skew the average, which would make your friends taller than you, on average. In this case, the “average” is a poor way to capture this data set.
Exactly this situation occurs on social networks. On average, your coauthors will be cited more often than you, and the people you follow will post more frequently than you, and so on.
Now Lerman from University of Southern California has discovered a related paradox, which they call the majority illusion. They illustrate this illusion with an example. They take 14 nodes linked up to form a small network. They then color three of these nodes and count how many of the remaining nodes link to them in a single step.
In one situation, the uncolored nodes see more than half of their neighbors as colored. This is the majority illusion — the local impression that a specific feature is common when the global truth is entirely different.
So how popular is it in the real world? It’s found out that the majority illusion occurs in almost all network scenarios. “The effect is largest in the political blogs network, where 60% of nodes will have majority active neighbours, even when only 20% of the nodes are truly active,” says Lerman.
It immediately explains many interesting phenomena. For a start, it shows how some content can spread globally while other similar content does not — the key is to start with a small number of well-connected early adopters fooling the rest of the network into thinking it is common. The affected nodes then find it natural to follow the trend. A real spread finally comes into being.
But it is not yet a marketer’s charter. For that, marketers must first identify the popular nodes that can create the majority illusion for the target audience. These influencers must then be persuaded to adopt the desired behavior or product, which is essential to the prospect of the marketing plan.
1. The phrase skew the average in the passage most probably refers to the action of ________.A.hiding the real average to be unrecognizable to others |
B.producing an average against the general feature of data |
C.working out the common feature suggested by the average |
D.ignoring the average because of the frequency by which it is reviewed |
A.Majority illusion rarely has impacts except in political blogs field. |
B.The majority illusion on social networks relies on that people you follow post more than you. |
C.The essence of successful opinion spread is to initiate the trend with well-connected sharers. |
D.The spread scale of ideas on networks mainly depends on the quality of content. |
A.thoroughly understand the concept of majority illusion |
B.accurately figure out who is the powerful person to affect others |
C.definitely decide who are the target audience for the promotion |
D.successfully convince the influencers to practice certain action |
A.The social network vision that tricks your mind. |
B.Who is stealing your network identity? |
C.Minority network opinion spread, curse or blessing? |
D.Have you been misled during the last political voting? |
9 . Why isn’t science better? Look at career incentives.
There are often substantial gaps between the idealized and actual versions of those people whose work involves providing a social good. Government officials are supposed to work for their constituents. Journalists are supposed to provide unbiased reporting and penetrating analysis. And scientists are supposed to relentlessly probe the fabric of reality with the most rigorous and skeptical of methods.
All too often, however, what should be just isn’t so. In a number of scientific fields, published findings turn out not to replicate (复制), or to have smaller effects than, what was initially claimed. Plenty of science does replicate — meaning the experiments turn out the same way when you repeat them — but the amount that doesn’t is too much for comfort.
But there are also ways in which scientists increase their chances of getting it wrong. Running studies with small samples, mining data for correlations and forming hypotheses to fit an experiment’s results after the fact are just some of the ways to increase the number of false discoveries.
It’s not like we don’t know how to do better. Scientists who study scientific methods have known about feasible remedies for decades. Unfortunately, their advice often falls on deaf ears. Why? Why aren’t scientific methods better than they are? In a word: incentives. But perhaps not in the way you think.
In the 1970s, psychologists and economists began to point out the danger in relying on quantitative measures for social decision-making. For example, when public schools are evaluated by students’ performance on standardized tests, teachers respond by teaching “to the test”. In turn, the test serves largely as of how well the school can prepare students for the test.
We can see this principle—often summarized as “when a measure becomes a target, it ceases to be a good measure”—playing out in the realm of research. Science is a competitive enterprise. There are far more credentialed (授以证书的) scholars and researchers than there are university professorships or comparably prestigious research positions. Once someone acquires a research position, there is additional competition for tenure (终身教授) grant funding, and support and placement for graduate students. Due to this competition for resources, scientists must be evaluated and compared. How do you tell if someone is a good scientist?
An oft-used metric (标准,度量) is the number of publications one has in peer-reviewed journals, as well as the status of those journals. Metrics like these make it straightforward to compare researchers whose work may otherwise be quite different. Unfortunately, this also makes these numbers susceptible to exploitation.
If scientists are motivated to publish often and in high-impact journals, we might expect them to actively try to game the system (钻空子). And certainly, some do—as seen in recent high-profile cases of scientific fraud (欺诈). If malicious (恶意的) fraud is the prime concern, then perhaps the solution is simply heightened alertness.
However, most scientists are, I believe, genuinely interested in learning about the world, and honest. The problem with incentives is that they can shape cultural norms without any intention on the part of individuals.
1. Which of the following is TRUE according to the passage?A.Scientists are expected to persistently devoted to exploration of reality. |
B.The research findings fail to achieve the expected effect. |
C.Hypotheses are modified to highlight the experiments’ results. |
D.The amount of science that does replicate is comforting. |
A.The public. | B.The incentive initiators. |
C.The peer researchers. | D.The high-impact journal editors. |
A.Good scientists excel in seeking resources and securing research positions. |
B.Competition for resources pushes researchers to publish in a more productive way. |
C.All the credentialed scholars and researchers will take up university professorships. |
D.The number of publication reveals how scientists are bitterly exploited. |
A.High-impact journals are encouraged to reform the incentives for publication. |
B.The peer-review process is supposed to scale up inspection of scientific fraud. |
C.Researchers are motivated to get actively involved in gaming the current system. |
D.Career incentives for scientists are expected to consider their personal intention. |
10 . During the initial stages of instructed L2 (the second language) acquisition students learn a couple thousand, mainly high frequency words. Functional language proficiency, however,
Acquisition of new words from authentic L2 reading texts by means of strategies such as contextual deduction (演绎) is also not a
Any suggestions on how to use this in educational contexts should be based on a systematic
A.inquires | B.requires | C.receives | D.inspires |
A.difficult | B.easy | C.possible | D.necessary |
A.copy | B.focus | C.find | D.clean |
A.however | B.moreover | C.because | D.nevertheless |
A.disturb | B.seem | C.occur | D.disappear |
A.solution | B.approach | C.problem | D.wonder |
A.official | B.annual | C.objective | D.alternative |
A.predicted | B.presented | C.postponed | D.preferred |
A.available | B.outstanding | C.attractive | D.evident |
A.by means of | B.moreover | C.in spite of | D.however |
A.focus | B.analysis | C.object | D.target |
A.describe | B.grasp | C.link | D.force |
A.conclusions | B.appointments | C.aspects | D.contents |
A.react | B.establish | C.memorize | D.leave |
A.enhanced | B.invented | C.contrasted | D.behaved |