一、Part Ⅱ Listening Comprehension
1、Question 1 is based on the conversation you have just heard.
A、Magazine reporter.
B、Fashion designer.
C、Website designer.
D、Features editor.
2、Question 2 is based on the conversation you have just heard.
A、Designing sports clothing.
B、Consulting fashion experts.
C、Answering daily emails.
D、Interviewing job-seekers.
3、Question 3 is based on the conversation you have just heard.
A、It is challenging.
B、It is fascinating.
C、It is tiresome.
D、It is fashionable.
4、Question 4 is based on the conversation you have just heard.
A、Her persistence.
B、Her experience.
C、Her competence.
D、Her confidence.
5、Question 5 is based on the conversation you have just heard.
A、It is enjoyable.
B、It is educational.
C、It is divorced from real life.
D、It is adapted from a drama.
6、Question 6 is based on the conversation you have just heard.
A、All the roles are played by famous actors and actresses.
B、It is based on the real-life experiences of some celebrities.
C、Its plots and events reveal a lot about Frankie’s actual life.
D、It is written, directed, edited and produced by Frankie himself.
7、Question 7 is based on the conversation you have just heard.
A、Go to the theater and enjoy it.
B、Recommend it to her friends.
C、Watch it with the man.
D、Download and watch it.
8、Question 8 is based on the conversation you have just heard.
A、It has drawn criticisms from scientists.
B、It has been showing for over a decade.
C、It is a ridiculous piece of satire.
D、It is against common sense.
9、Question 9 is based on the passage you have just heard.
A、They are likely to get injured when moving too fast.
B、They believe in team spirit for good performance.
C、They need to keep moving to avoid getting hurt.
D、They have to learn how to avoid body contact.
10、Question 10 is based on the passage you have just heard.
A、They do not have many years to live after retirement.
B、They tend to live longer life with early retirement.
C、They do not start enjoying life until full retirement.
D、They keep themselves busy even after retirement.
11、Question 11 is based on the passage you have just heard.
A、It prevents us from worrying.
B、It slows down our aging process.
C、It enables us to accomplish more in life.
D、It provides us with more chances to learn.
12、Question 12 is based on the passage you have just heard.
A、It tends to dwell upon their joyous experiences.
B、It wanders for almost half of their waking time.
C、It has trouble concentrating after a brain injury.
D、It tends to be affected by their negative feelings.
13、Question 13 is based on the passage you have just heard.
A、To find how happiness relates to daydreaming.
B、To observe how one’s mind affects one’s behavior.
C、To see why daydreaming impacts what one is doing.
D、To study the relation between health and daydreaming.
14、Question 14 is based on the passage you have just heard.
A、It helps them make good decisions.
B、It helps them tap their potentials.
C、It contributes to their creativity.
D、It contributes to clear thinking.
15、Question 15 is based on the passage you have just heard.
A、Subjects with clear goals in mind outperformed those without clear goals.
B、The difference in performance between the two groups was insignificant.
C、Non-daydreamers were more focused on their tasks than daydreamers.
D、Daydreamers did better than non-daydreamers in task performance.
16、Question 16 is based on the recording you have just heard.
A、They are the oldest buildings in Europe.
B、They are part of the Christian tradition.
C、They are renovated to attract tourists.
D、They are in worsening condition.
17、Question 17 is based on the recording you have just heard.
A、They have a history of 14 centuries.
B、They are 40 metres tall on average.
C、They are without foundations.
D、They consist of several storeys.
18、Question 18 is based on the recording you have just heard.
A、Wood was harmonious with nature.
B、Wooden buildings kept the cold out.
C、Timber was abundant in Scandinavia.
D、The Vikings liked wooden structures.
19、Question 19 is based on the recording you have just heard.
A、Similarities between human babies and baby animals.
B、Cognitive features of different newly born mammals.
C、Adults’ influence on children.
D、Abilities of human babies.
20、Question 20 is based on the recording you have just heard.
A、They can distinguish a happy tune from a sad one.
B、They love happy melodies more than sad ones.
C、They fall asleep easily while listening to music.
D、They are already sensitive to beats and rhythms.
21、Question 21 is based on the recording you have just heard.
A、Infants’ facial expressions.
B、Babies’ emotions.
C、Babies’ interaction with adults.
D、Infants’ behaviors.
22、Question 22 is based on the recording you have just heard.
A、It may harm the culture of today’s workplace.
B、It may hinder individual career advancement.
C、It may result in unwillingness to take risks.
D、It may put too much pressure on team members.
23、Question 23 is based on the recording you have just heard.
A、They can hardly give expression to their original views.
B、They can become less motivated to do projects of their own.
C、They may find it hard to get their contributions recognized.
D、They may eventually lose their confidence and creativity.
24、Question 24 is based on the recording you have just heard.
A、They can enlarge their professional circle.
B、They can get chances to engage in research.
C、They can make the best use of their expertise.
D、They can complete the project more easily.
25、Question 25 is based on the recording you have just heard.
A、It may cause lots of arguments in a team.
B、It may prevent making a timely decision.
C、It may give rise to a lot of unnecessary expenses.
D、It may deprive a team of business opportunities.
二、Part III Reading Comprehension
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
26、(1)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
27、(2)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
28、(3)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
29、(4)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
30、(5)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
31、(6)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
32、(7)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
33、(8)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
34、(9)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
When considering risk factors associated with serious chronic diseases, we often think about health indicators such as cholesterol, blood pressure, and body weight. But poor diet and physical inactivity also each increase the risk of heart disease and have a role to play in the development of some cancers. Perhaps worse, the (26)_____ effects of an unhealthy diet and insufficient exercise are not limited to your body. Recent research has also shown that (27)_____ in a high-fat and high-sugar diet may have negative effects on your brain, causing learning and memory (28)_____.
Studies have found obesity is associated with impairments in cognitive functioning, as (29)_____ by a range of learning and memory tests, such as the ability to remember a list of words presented some minutes or hours earlier. There is also a growing body of evidence that diet-induced cognitive impairments can emerge (30)_____—within weeks or even days. For example, one study found healthy adults (31)_____ to a high-fat diet for five days showed impaired attention, memory, and mood compared with a low-fat diet control group. Another study also found eating a high-fat and high-sugar breakfast each day for as little as four days resulted in problems with learning and memory (32)_____ to those observed in overweight and obese individuals.
Body weight was not hugely different between the groups eating a healthy diet and those on high fat and sugar diets. So this shows negative (33)_____ of poor dietary intake can occur even when body weight has not changed (34)_____. Thus, body weight is not always the best indicator of health and a thin person still needs to eat well and exercise (35)_____.
35、(10)
A、similar
B、conspicuously
C、consequences
D、designated
E、assessed
F、indulging
G、regularly
H、loopholes
I、detrimental
J、assigned
K、deficits
L、digestion
M、redundant
N、excelling
O、rapidly
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
36、
36. The year when most Americans began using smartphones was identified as a turning point in young Americans’ level of happiness.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
37、
37. Scores in various wellbeing measures began to go downward among young Americans in recent years.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
38、
38. Unfortunately, activities involving direct contact with people, which contributed to better wellbeing, were found to be on the decline.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
39、
39. In response to past critics, Twenge and her co-researchers stress they are not trying to prove that the use of digital devices reduces young people’s wellbeing.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
40、
40. In the last few decades of the 20th century, living standards went up and economic depressions were largely averted in the US.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
41、
41. Contrary to popular belief, doing homework might add to students’ wellbeing.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
42、
42. The author believes the researchers’ new study has gone a step further regarding the impact of screen time on wellbeing.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
43、
43. The researchers found that extended screen time makes young people less happy.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
44、
44. Data reveals that economic inequality rather than family income might affect people’s wellbeing.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
Increased Screen Time and Wellbeing Decline in Youth
【A】Have young people never had it so good? Or do they face more challenges than any previous generation? Our current era in the West is one of high wealth. This means minors enjoy material benefits and legal protections that would have been the envy of those living in the past. But there is an increasing suspicion that all is not well for our youth. And one of the most popular explanations, among some experts and the popular media, is that excessive “screen time” is to blame. (This refers to all the attention young people devote to their phones, tablets and laptops.) However, this is a contentious theory and such claims have been treated skeptically by some scholars based on their reading of the relevant data.
【B】Now a new study has provided another contribution to the debate, uncovering strong evidence that adolescent wellbeing in the United States really is experiencing a decline and arguing that the most likely cause is the electronic riches we have given them. The background to this is that from the 1960s into the early 2000s, measures of average wellbeing went up in the US. This was especially true for younger people. It reflected the fact that these decades saw a climb in general standards of living and avoidance of mass societal traumas like full-scale war or economic deprivation. However, the “screen time” hypothesis, advanced by researchers such as Jean Twenge, is that electronic devices and excessive time spent online may have reversed these trends in recent years, causing problems for young people’s psychological health.
【C】To investigate, Twenge and her colleagues dived into the “Monitoring the Future” dataset based on annual surveys of American school students from grades 8, 10, and 12 that started in 1991. In total, 1.1 million young people answered various questions related to their wellbeing. Twenge’s team’s analysis of the answers confirmed the earlier, well-established wellbeing climb, with scores rising across the 1990s, and into the later 2000s. This was found across measures like self-esteem, life satisfaction, happiness and satisfaction with individual domains like job, neighborhood, or friends. But around 2012 these measures started to decline. This continued through 2016, the most recent year for which data is available.
【D】Twenge and her colleagues wanted to understand why this change in average wellbeing occurred. However, it is very hard to demonstrate causes using non-experimental data such as this. In fact, when Twenge previously used this data to suggest a screen time effect, some commentators were quick to raise this problem. They argued that her causal-sounding claims rested on correlational data, and that she had not adequately accounted for other potential causal factors. This time around, Twenge and her team make a point of saying that they are not trying to establish causes as such, but that they are assessing the plausibility of potential causes.
【E】First, they explain that if a given variable is playing a role in affecting wellbeing, then we should expect any change in that variable to correlate with the observed changes in wellbeing. If not, it is not plausible that the variable is a causal factor. So the researchers looked at time spent in a number of activities that could plausibly be driving the wellbeing decline. Less sport, and fewer meetings with peers correlated with lower wellbeing, as did less time reading print media (newspapers) and, surprisingly, less time doing homework. (This last finding would appear to contradict another popular hypothesis that it is our burdening of students with assignments that is causing all the problems.) In addition, more TV watching and more electronic communication both correlated with lower wellbeing. All these effects held true for measures of happiness, life satisfaction and self-esteem, with the effects stronger in the 8th and 10th-graders.
【F】Next, Twenge’s team dug a little deeper into the data on screen time. They found that adolescents who spent a very small amount of time on digital devices—a couple of hours a week—had the highest wellbeing. Their wellbeing was even higher than those who never used such devices. However, higher doses of screen time were clearly associated with lower happiness. Those spending 10-19 hours per week on their devices were 41 percent more likely to be unhappy than lower-frequency users. Those who used such devices 40 hours a week or more (one in ten teenagers) were twice as likely to be unhappy. The data was slightly complicated by the fact that there was a tendency for kids who were social in the real world to also use more online communication, but by bracketing out different cases it became clear that the real-world sociality component correlated with greater wellbeing, whereas greater time on screens or online only correlated with poorer wellbeing.
【G】So far, so plausible. But the next question is, are the drops in average wellbeing happening at the same time as trends toward increased electronic device usage? It looks like it—after all, 2012 was the tipping point when more than half of Americans began owning smartphones. Twenge and her colleagues also found that across the key years of 2013-16, wellbeing was indeed lowest in years where adolescents spent more time online, on social media, and reading news online, and when more youth in the United States had smartphones. And in a second analysis, they found that where technology went, dips in wellbeing followed. For instance, years with a larger increase in online usage were followed by years with lower wellbeing, rather than the other way around. This does not prove causality, but is consistent with it. Meanwhile, TV use did not show this tracking. TV might make you less happy, but this is not what seems to be driving the recent declines in young people’s average happiness.
【H】A similar but reversed pattern was found for the activities associated with greater wellbeing. For example, years when people spent more time with friends were better years for wellbeing (and followed by better years). Sadly, the data also showed face-to-face socializing and sports activity had declined over the period covered by the survey.
【I】There is another explanation that Twenge and her colleagues wanted to address: the impact of the the great recession of 2007-2009, which hit a great number of American families and might be affecting adolescents. The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators. They found some evidence that some crude measures, like income inequality, correlated with changes in wellbeing, but economic measures with a more direct impact, like family income and unemployment rates (which put families into difficulties), had no relationship with wellbeing. The researchers also note that the recession hit some years before we see the beginning of the wellbeing drop, and before the steepest wellbeing decline, which occurred in 2013.
【J】The researchers conclude that electronic communication was the only adolescent activity that increased at the same time psychological wellbeing declined. I suspect that some experts in the field will be keen to address alternative explanations, such as unassessed variables playing a role in the wellbeing decline. But the new work does go further than previous research and suggests that screen time should still be considered a potential barrier to young people’s flourishing.
45、
45. Too much screen time is widely believed to be the cause of unhappiness among today’s young people.
A、A
B、B
C、C
D、D
E、E
F、F
G、G
H、H
I、I
J、J
“The dangerous thing about lying is people don’t understand how the act changes us,” says Dan Ariely, behavioural psychologist at Duke University. Psychologists have documented children lying as early as the age of two. Some experts even consider lying a developmental milestone, like crawling and walking, because it requires sophisticated planning, attention and the ability to see a situation from someone else’s perspective to manipulate them. But, for most people, lying gets limited as we develop a sense of morality and the ability to self-regulate.
Harvard cognitive neuroscientist Joshua Greene says, for most of us, lying takes work. In studies, he gave subjects a chance to deceive for monetary gain while examining their brains in a functional MRI machine, which maps blood flow to active parts of the brain. Some people told the truth instantly and instinctively. But others opted to lie, and they showed increased activity in their frontal parietal (颅腔壁的) control network, which is involved in difficult or complex thinking. This suggests that they were deciding between truth and dishonesty—and ultimately opting for the latter. For a follow-up analysis, he found that people whose neural (神经的) reward centers were more active when they won money were also more likely to be among the group of liars—suggesting that lying may have to do with the inability to resist temptation.
External conditions also matter in terms of when and how often we lie. We are more likely to lie, research shows, when we are able to rationalise it, when we are stressed and fatigued or see others being dishonest. And we are less likely to lie when we have moral reminders or when we think others are watching. “We as a society need to understand that, when we don’t punish lying, we increase the probability it will happen again,” Ariely says.
In a 2016 study published in the journal Nature Neuroscience, Ariely and colleagues showed how dishonesty alters people’s brains, making it easier to tell lies in the future. When people uttered a falsehood, the scientists noticed a burst of activity in their amygdala. The amygdala is a crucial part of the brain that produces fear, anxiety and emotional responses—including that sinking, guilty feeling you get when you lie. But when scientists had their subjects play a game in which they won money by deceiving their partner, they noticed the negative signals from the amygdala began to decrease. Not only that, but when people faced no consequences for dishonesty, their falsehoods tended to get even more sensational. This means that if you give people multiple opportunities to lie for their own benefit, they start with little lies which get bigger over time.
46、46. Why do some experts consider lying a milestone in a child’s development?
A、It shows they have the ability to view complex situations from different angles.
B、It indicates they have an ability more remarkable than crawling and walking.
C、It represents their ability to actively interact with people around them.
D、It involves the coordination of both their mental and physical abilities.
“The dangerous thing about lying is people don’t understand how the act changes us,” says Dan Ariely, behavioural psychologist at Duke University. Psychologists have documented children lying as early as the age of two. Some experts even consider lying a developmental milestone, like crawling and walking, because it requires sophisticated planning, attention and the ability to see a situation from someone else’s perspective to manipulate them. But, for most people, lying gets limited as we develop a sense of morality and the ability to self-regulate.
Harvard cognitive neuroscientist Joshua Greene says, for most of us, lying takes work. In studies, he gave subjects a chance to deceive for monetary gain while examining their brains in a functional MRI machine, which maps blood flow to active parts of the brain. Some people told the truth instantly and instinctively. But others opted to lie, and they showed increased activity in their frontal parietal (颅腔壁的) control network, which is involved in difficult or complex thinking. This suggests that they were deciding between truth and dishonesty—and ultimately opting for the latter. For a follow-up analysis, he found that people whose neural (神经的) reward centers were more active when they won money were also more likely to be among the group of liars—suggesting that lying may have to do with the inability to resist temptation.
External conditions also matter in terms of when and how often we lie. We are more likely to lie, research shows, when we are able to rationalise it, when we are stressed and fatigued or see others being dishonest. And we are less likely to lie when we have moral reminders or when we think others are watching. “We as a society need to understand that, when we don’t punish lying, we increase the probability it will happen again,” Ariely says.
In a 2016 study published in the journal Nature Neuroscience, Ariely and colleagues showed how dishonesty alters people’s brains, making it easier to tell lies in the future. When people uttered a falsehood, the scientists noticed a burst of activity in their amygdala. The amygdala is a crucial part of the brain that produces fear, anxiety and emotional responses—including that sinking, guilty feeling you get when you lie. But when scientists had their subjects play a game in which they won money by deceiving their partner, they noticed the negative signals from the amygdala began to decrease. Not only that, but when people faced no consequences for dishonesty, their falsehoods tended to get even more sensational. This means that if you give people multiple opportunities to lie for their own benefit, they start with little lies which get bigger over time.
47、47. Why does the Harvard neuroscientist say that lying takes work?
A、It is hard to choose from several options.
B、It is difficult to sound natural or plausible.
C、It requires speedy blood flow into one’s brain.
D、It involves lots of sophisticated mental activity.
“The dangerous thing about lying is people don’t understand how the act changes us,” says Dan Ariely, behavioural psychologist at Duke University. Psychologists have documented children lying as early as the age of two. Some experts even consider lying a developmental milestone, like crawling and walking, because it requires sophisticated planning, attention and the ability to see a situation from someone else’s perspective to manipulate them. But, for most people, lying gets limited as we develop a sense of morality and the ability to self-regulate.
Harvard cognitive neuroscientist Joshua Greene says, for most of us, lying takes work. In studies, he gave subjects a chance to deceive for monetary gain while examining their brains in a functional MRI machine, which maps blood flow to active parts of the brain. Some people told the truth instantly and instinctively. But others opted to lie, and they showed increased activity in their frontal parietal (颅腔壁的) control network, which is involved in difficult or complex thinking. This suggests that they were deciding between truth and dishonesty—and ultimately opting for the latter. For a follow-up analysis, he found that people whose neural (神经的) reward centers were more active when they won money were also more likely to be among the group of liars—suggesting that lying may have to do with the inability to resist temptation.
External conditions also matter in terms of when and how often we lie. We are more likely to lie, research shows, when we are able to rationalise it, when we are stressed and fatigued or see others being dishonest. And we are less likely to lie when we have moral reminders or when we think others are watching. “We as a society need to understand that, when we don’t punish lying, we increase the probability it will happen again,” Ariely says.
In a 2016 study published in the journal Nature Neuroscience, Ariely and colleagues showed how dishonesty alters people’s brains, making it easier to tell lies in the future. When people uttered a falsehood, the scientists noticed a burst of activity in their amygdala. The amygdala is a crucial part of the brain that produces fear, anxiety and emotional responses—including that sinking, guilty feeling you get when you lie. But when scientists had their subjects play a game in which they won money by deceiving their partner, they noticed the negative signals from the amygdala began to decrease. Not only that, but when people faced no consequences for dishonesty, their falsehoods tended to get even more sensational. This means that if you give people multiple opportunities to lie for their own benefit, they start with little lies which get bigger over time.
48、48. Under what circumstances do people tend to lie?
A、When they become too emotional.
B、When they face too much peer pressure.
C、When the temptation is too strong.
D、When the consequences are not imminent.
“The dangerous thing about lying is people don’t understand how the act changes us,” says Dan Ariely, behavioural psychologist at Duke University. Psychologists have documented children lying as early as the age of two. Some experts even consider lying a developmental milestone, like crawling and walking, because it requires sophisticated planning, attention and the ability to see a situation from someone else’s perspective to manipulate them. But, for most people, lying gets limited as we develop a sense of morality and the ability to self-regulate.
Harvard cognitive neuroscientist Joshua Greene says, for most of us, lying takes work. In studies, he gave subjects a chance to deceive for monetary gain while examining their brains in a functional MRI machine, which maps blood flow to active parts of the brain. Some people told the truth instantly and instinctively. But others opted to lie, and they showed increased activity in their frontal parietal (颅腔壁的) control network, which is involved in difficult or complex thinking. This suggests that they were deciding between truth and dishonesty—and ultimately opting for the latter. For a follow-up analysis, he found that people whose neural (神经的) reward centers were more active when they won money were also more likely to be among the group of liars—suggesting that lying may have to do with the inability to resist temptation.
External conditions also matter in terms of when and how often we lie. We are more likely to lie, research shows, when we are able to rationalise it, when we are stressed and fatigued or see others being dishonest. And we are less likely to lie when we have moral reminders or when we think others are watching. “We as a society need to understand that, when we don’t punish lying, we increase the probability it will happen again,” Ariely says.
In a 2016 study published in the journal Nature Neuroscience, Ariely and colleagues showed how dishonesty alters people’s brains, making it easier to tell lies in the future. When people uttered a falsehood, the scientists noticed a burst of activity in their amygdala. The amygdala is a crucial part of the brain that produces fear, anxiety and emotional responses—including that sinking, guilty feeling you get when you lie. But when scientists had their subjects play a game in which they won money by deceiving their partner, they noticed the negative signals from the amygdala began to decrease. Not only that, but when people faced no consequences for dishonesty, their falsehoods tended to get even more sensational. This means that if you give people multiple opportunities to lie for their own benefit, they start with little lies which get bigger over time.
49、49. When are people less likely to lie?
A、When they are worn out and stressed.
B、When they are under watchful eyes.
C、When they think in a rational way.
D、When they have a clear conscience.
“The dangerous thing about lying is people don’t understand how the act changes us,” says Dan Ariely, behavioural psychologist at Duke University. Psychologists have documented children lying as early as the age of two. Some experts even consider lying a developmental milestone, like crawling and walking, because it requires sophisticated planning, attention and the ability to see a situation from someone else’s perspective to manipulate them. But, for most people, lying gets limited as we develop a sense of morality and the ability to self-regulate.
Harvard cognitive neuroscientist Joshua Greene says, for most of us, lying takes work. In studies, he gave subjects a chance to deceive for monetary gain while examining their brains in a functional MRI machine, which maps blood flow to active parts of the brain. Some people told the truth instantly and instinctively. But others opted to lie, and they showed increased activity in their frontal parietal (颅腔壁的) control network, which is involved in difficult or complex thinking. This suggests that they were deciding between truth and dishonesty—and ultimately opting for the latter. For a follow-up analysis, he found that people whose neural (神经的) reward centers were more active when they won money were also more likely to be among the group of liars—suggesting that lying may have to do with the inability to resist temptation.
External conditions also matter in terms of when and how often we lie. We are more likely to lie, research shows, when we are able to rationalise it, when we are stressed and fatigued or see others being dishonest. And we are less likely to lie when we have moral reminders or when we think others are watching. “We as a society need to understand that, when we don’t punish lying, we increase the probability it will happen again,” Ariely says.
In a 2016 study published in the journal Nature Neuroscience, Ariely and colleagues showed how dishonesty alters people’s brains, making it easier to tell lies in the future. When people uttered a falsehood, the scientists noticed a burst of activity in their amygdala. The amygdala is a crucial part of the brain that produces fear, anxiety and emotional responses—including that sinking, guilty feeling you get when you lie. But when scientists had their subjects play a game in which they won money by deceiving their partner, they noticed the negative signals from the amygdala began to decrease. Not only that, but when people faced no consequences for dishonesty, their falsehoods tended to get even more sensational. This means that if you give people multiple opportunities to lie for their own benefit, they start with little lies which get bigger over time.
50、50. What does the author say will happen when a liar does not get punished?
A、They may feel justified.
B、They will tell bigger lies.
C、They will become complacent.
D、They may mix lies and truths.
Here’s how the Pacific Northwest is preparing for “The Big One”. It’s the mother of all disaster drills for what could be the worst disaster in American history. California has spent years preparing for “The Big One”—the inevitable earthquake that will undoubtedly unleash all kinds of havoc along the famous San Andreas fault (断层). But what if the fault that runs along the Pacific Northwest delivers a gigantic earthquake of its own? If the people of the Cascadia region have anything to do with it, they won’t be caught unawares.
The region is engaged in a multi-day earthquake-and-tsunami (海啸) drill involving around 20,000 people. The Cascadia Rising drill gives area residents and emergency responders a chance to practice what to do in case of a 9.0-magnitude earthquake and tsunami along one of the nation’s dangerous—and underestimated—faults.
The Cascadia Earthquake Zone is big enough to compete with San Andreas (it’s been called the most dangerous fault in America), but it’s much lesser known than its California cousin. Nearly 700 miles long, the earthquake zone is located by the North American Plate off the coast of Pacific British Columbia, Washington, Oregon and Northern California.
Cascadia is what’s known as a “megathrust” fault. Megathrusts are created in earthquake zones—land plate boundaries where two plates converge. In the areas where one plate is beneath another, stress builds up over time. During a megathrust event, all of that stress releases and some of the world’s most powerful earthquakes occur. Remember the 9.1 earthquake and tsunami in the Indian Ocean off Sumatra in 2004? It was caused by a megathrust event as the India plate moved beneath the Burma micro-plate.
The last time a major earthquake occurred along the Cascadia fault was in 1700, so officials worry that another event could occur any time. To prevent that event from becoming a catastrophe, first responders will join members of the public in rehearsals that involve communication, evacuation, search and rescue, and other scenarios.
Thousands of casualties are expected if a 9.0 earthquake were to occur. First, the earthquake would shake metropolitan areas including Seattle and Portland. This could trigger a tsunami that would create havoc along the coast. Not all casualties can necessarily be prevented—but by coordinating across local, state, and even national borders, officials hope that the worst-case scenario can be averted. On the exercise’s website, officials explain that the report they prepare during this rehearsal will inform disaster management for years to come.
For hundreds of thousands of Cascadia residents, “The Big One” isn’t a question of if, only when. And it’s never too early to get ready for the inevitable.
51、51. What does “The Big One” refer to?
A、A gigantic geological fault.
B、A large-scale exercise to prepare for disasters.
C、A massive natural catastrophe.
D、A huge tsunami on the California coast.
Here’s how the Pacific Northwest is preparing for “The Big One”. It’s the mother of all disaster drills for what could be the worst disaster in American history. California has spent years preparing for “The Big One”—the inevitable earthquake that will undoubtedly unleash all kinds of havoc along the famous San Andreas fault (断层). But what if the fault that runs along the Pacific Northwest delivers a gigantic earthquake of its own? If the people of the Cascadia region have anything to do with it, they won’t be caught unawares.
The region is engaged in a multi-day earthquake-and-tsunami (海啸) drill involving around 20,000 people. The Cascadia Rising drill gives area residents and emergency responders a chance to practice what to do in case of a 9.0-magnitude earthquake and tsunami along one of the nation’s dangerous—and underestimated—faults.
The Cascadia Earthquake Zone is big enough to compete with San Andreas (it’s been called the most dangerous fault in America), but it’s much lesser known than its California cousin. Nearly 700 miles long, the earthquake zone is located by the North American Plate off the coast of Pacific British Columbia, Washington, Oregon and Northern California.
Cascadia is what’s known as a “megathrust” fault. Megathrusts are created in earthquake zones—land plate boundaries where two plates converge. In the areas where one plate is beneath another, stress builds up over time. During a megathrust event, all of that stress releases and some of the world’s most powerful earthquakes occur. Remember the 9.1 earthquake and tsunami in the Indian Ocean off Sumatra in 2004? It was caused by a megathrust event as the India plate moved beneath the Burma micro-plate.
The last time a major earthquake occurred along the Cascadia fault was in 1700, so officials worry that another event could occur any time. To prevent that event from becoming a catastrophe, first responders will join members of the public in rehearsals that involve communication, evacuation, search and rescue, and other scenarios.
Thousands of casualties are expected if a 9.0 earthquake were to occur. First, the earthquake would shake metropolitan areas including Seattle and Portland. This could trigger a tsunami that would create havoc along the coast. Not all casualties can necessarily be prevented—but by coordinating across local, state, and even national borders, officials hope that the worst-case scenario can be averted. On the exercise’s website, officials explain that the report they prepare during this rehearsal will inform disaster management for years to come.
For hundreds of thousands of Cascadia residents, “The Big One” isn’t a question of if, only when. And it’s never too early to get ready for the inevitable.
52、52. What is the purpose of the Cascadia Rising drill?
A、To prepare people for a major earthquake and tsunami.
B、To increase residents’ awareness of imminent disasters.
C、To teach people how to adapt to post-disaster life.
D、To cope with the aftermath of a possible earthquake.
Here’s how the Pacific Northwest is preparing for “The Big One”. It’s the mother of all disaster drills for what could be the worst disaster in American history. California has spent years preparing for “The Big One”—the inevitable earthquake that will undoubtedly unleash all kinds of havoc along the famous San Andreas fault (断层). But what if the fault that runs along the Pacific Northwest delivers a gigantic earthquake of its own? If the people of the Cascadia region have anything to do with it, they won’t be caught unawares.
The region is engaged in a multi-day earthquake-and-tsunami (海啸) drill involving around 20,000 people. The Cascadia Rising drill gives area residents and emergency responders a chance to practice what to do in case of a 9.0-magnitude earthquake and tsunami along one of the nation’s dangerous—and underestimated—faults.
The Cascadia Earthquake Zone is big enough to compete with San Andreas (it’s been called the most dangerous fault in America), but it’s much lesser known than its California cousin. Nearly 700 miles long, the earthquake zone is located by the North American Plate off the coast of Pacific British Columbia, Washington, Oregon and Northern California.
Cascadia is what’s known as a “megathrust” fault. Megathrusts are created in earthquake zones—land plate boundaries where two plates converge. In the areas where one plate is beneath another, stress builds up over time. During a megathrust event, all of that stress releases and some of the world’s most powerful earthquakes occur. Remember the 9.1 earthquake and tsunami in the Indian Ocean off Sumatra in 2004? It was caused by a megathrust event as the India plate moved beneath the Burma micro-plate.
The last time a major earthquake occurred along the Cascadia fault was in 1700, so officials worry that another event could occur any time. To prevent that event from becoming a catastrophe, first responders will join members of the public in rehearsals that involve communication, evacuation, search and rescue, and other scenarios.
Thousands of casualties are expected if a 9.0 earthquake were to occur. First, the earthquake would shake metropolitan areas including Seattle and Portland. This could trigger a tsunami that would create havoc along the coast. Not all casualties can necessarily be prevented—but by coordinating across local, state, and even national borders, officials hope that the worst-case scenario can be averted. On the exercise’s website, officials explain that the report they prepare during this rehearsal will inform disaster management for years to come.
For hundreds of thousands of Cascadia residents, “The Big One” isn’t a question of if, only when. And it’s never too early to get ready for the inevitable.
53、53. What happens in case of a megathrust earthquake according to the passage?
A、Two plates merge into one.
B、A variety of forces converge.
C、Boundaries blur between plates.
D、Enormous stress is released.
Here’s how the Pacific Northwest is preparing for “The Big One”. It’s the mother of all disaster drills for what could be the worst disaster in American history. California has spent years preparing for “The Big One”—the inevitable earthquake that will undoubtedly unleash all kinds of havoc along the famous San Andreas fault (断层). But what if the fault that runs along the Pacific Northwest delivers a gigantic earthquake of its own? If the people of the Cascadia region have anything to do with it, they won’t be caught unawares.
The region is engaged in a multi-day earthquake-and-tsunami (海啸) drill involving around 20,000 people. The Cascadia Rising drill gives area residents and emergency responders a chance to practice what to do in case of a 9.0-magnitude earthquake and tsunami along one of the nation’s dangerous—and underestimated—faults.
The Cascadia Earthquake Zone is big enough to compete with San Andreas (it’s been called the most dangerous fault in America), but it’s much lesser known than its California cousin. Nearly 700 miles long, the earthquake zone is located by the North American Plate off the coast of Pacific British Columbia, Washington, Oregon and Northern California.
Cascadia is what’s known as a “megathrust” fault. Megathrusts are created in earthquake zones—land plate boundaries where two plates converge. In the areas where one plate is beneath another, stress builds up over time. During a megathrust event, all of that stress releases and some of the world’s most powerful earthquakes occur. Remember the 9.1 earthquake and tsunami in the Indian Ocean off Sumatra in 2004? It was caused by a megathrust event as the India plate moved beneath the Burma micro-plate.
The last time a major earthquake occurred along the Cascadia fault was in 1700, so officials worry that another event could occur any time. To prevent that event from becoming a catastrophe, first responders will join members of the public in rehearsals that involve communication, evacuation, search and rescue, and other scenarios.
Thousands of casualties are expected if a 9.0 earthquake were to occur. First, the earthquake would shake metropolitan areas including Seattle and Portland. This could trigger a tsunami that would create havoc along the coast. Not all casualties can necessarily be prevented—but by coordinating across local, state, and even national borders, officials hope that the worst-case scenario can be averted. On the exercise’s website, officials explain that the report they prepare during this rehearsal will inform disaster management for years to come.
For hundreds of thousands of Cascadia residents, “The Big One” isn’t a question of if, only when. And it’s never too early to get ready for the inevitable.
54、54. What do the officials hope to achieve through the drills?
A、Coordinating various disaster-relief efforts.
B、Reducing casualties in the event of a disaster.
C、Minimizing property loss caused by disasters.
D、Establishing disaster and emergency management.
Here’s how the Pacific Northwest is preparing for “The Big One”. It’s the mother of all disaster drills for what could be the worst disaster in American history. California has spent years preparing for “The Big One”—the inevitable earthquake that will undoubtedly unleash all kinds of havoc along the famous San Andreas fault (断层). But what if the fault that runs along the Pacific Northwest delivers a gigantic earthquake of its own? If the people of the Cascadia region have anything to do with it, they won’t be caught unawares.
The region is engaged in a multi-day earthquake-and-tsunami (海啸) drill involving around 20,000 people. The Cascadia Rising drill gives area residents and emergency responders a chance to practice what to do in case of a 9.0-magnitude earthquake and tsunami along one of the nation’s dangerous—and underestimated—faults.
The Cascadia Earthquake Zone is big enough to compete with San Andreas (it’s been called the most dangerous fault in America), but it’s much lesser known than its California cousin. Nearly 700 miles long, the earthquake zone is located by the North American Plate off the coast of Pacific British Columbia, Washington, Oregon and Northern California.
Cascadia is what’s known as a “megathrust” fault. Megathrusts are created in earthquake zones—land plate boundaries where two plates converge. In the areas where one plate is beneath another, stress builds up over time. During a megathrust event, all of that stress releases and some of the world’s most powerful earthquakes occur. Remember the 9.1 earthquake and tsunami in the Indian Ocean off Sumatra in 2004? It was caused by a megathrust event as the India plate moved beneath the Burma micro-plate.
The last time a major earthquake occurred along the Cascadia fault was in 1700, so officials worry that another event could occur any time. To prevent that event from becoming a catastrophe, first responders will join members of the public in rehearsals that involve communication, evacuation, search and rescue, and other scenarios.
Thousands of casualties are expected if a 9.0 earthquake were to occur. First, the earthquake would shake metropolitan areas including Seattle and Portland. This could trigger a tsunami that would create havoc along the coast. Not all casualties can necessarily be prevented—but by coordinating across local, state, and even national borders, officials hope that the worst-case scenario can be averted. On the exercise’s website, officials explain that the report they prepare during this rehearsal will inform disaster management for years to come.
For hundreds of thousands of Cascadia residents, “The Big One” isn’t a question of if, only when. And it’s never too early to get ready for the inevitable.
55、55. What does the author say about “The Big One”?
A、Whether it will occur remains to be seen.
B、How it will arrive is too early to predict.
C、Its occurrence is just a matter of time.
D、It keeps haunting Cascadia residents.
三、Part IV Translation
56、
荷花（lotus flower）是中国的名花之一，深受人们喜爱。中国许多地方的湖泊和池塘都适宜荷花生长。荷花颜色鲜艳，夏日清晨绽放，夜晚闭合，花期长达两三个月，吸引来自各地的游客前往观赏。荷花具有多种功能，既能绿化水面，又能美化庭院，还可净化水质、减少污染、改善环境。荷花迎骄阳而不惧，出污泥而不染，象征纯洁、高雅，常常用来比喻人的高尚品德，历来是诗人画家创作的重要题材。荷花盛开的地方也是许多摄影爱好者经常光顾之地。
参考答案：
参考译文
Deeply beloved by people, lotus flower is one of the best-known flowers in China. Many lakes and ponds in China are suitable for lotuses to grow. Bright in color, lotus blossoms in the morning and closes at night on summer days. With a flowering phase of two to three months, lotus attracts tourists from all over the country. As a multi-functional plant, lotus can green water surface, beautify yards, purify water, reduce pollution as well as improve the environment. Lotus is neither fearing the burning sunlight nor being polluted by the mud, and it is a symbol of purity and elegance, making it a metaphor for one’s noble virtues. Lotus has long been an important theme for the creation of poets and painters. The places where lotuses bloom are also attractions for many photography lovers.
四、Part I Writing
57、
Directions: For this part, you are allowed 30 minutes to write an essay on the importance of having a sense of social responsibility. You should write at least 150 words but no more than 200 words.
参考答案：
参考范文
In today’s society, irresponsible incidents take place from time to time, which is a grave problem we are all facing. Therefore, the topic of social responsibility has been discussed heatedly. From my perspective, not only is social responsibility of great significance to society, but it is of benefit to the individuals.
There are several reasons that can justify my argument. To begin with, we should be aware that each of us belongs to society and everything we do affects society. Thus, we are obligated to behave responsibly in every aspect of life to secure the safety and progress of society. For example, we should obey laws, protect the environment, pay taxes on time, and offer help to people in need. Besides, these good deeds in our lives can certainly pay back to us as we can enjoy fresh air and water, feel respected and be offered help when we ourselves are in need.
To sum up, shouldering social responsibilities has many positive effects on social development as well as personal growth. We should all have a sense of social responsibility as it not only cultivates our personalities, but also accelerates social progress if more of us have it.
参考译文
当今社会，不负责任的事件时有发生，这是我们都会面临的一个严峻问题。因此，社会责任感这一话题一直热议不断。在我看来，社会责任感不仅对社会意义重大，对个人也大有裨益。
有几点原因可以证明我的观点。首先，我们应该明白我们每个人都是社会的一员，我们做的每件事都会影响社会。所以，我们有义务在生活的每个方面都负起责任，这样才能保证社会的安全和进步。比如说，我们应当遵守法律、保护环境、按时缴税、帮助他人。另外，生活中这些好的行为也会给我们带来回报：我们可以享受清洁的空气和水资源，受到别人的尊重，并且在我们需要帮助的时候也会有人施以援手。
总而言之，承担社会责任对于社会发展和个人成长有很多积极作用。我们每个人都应该怀有这种社会责任感，因为它不仅可以培养我们的品格，还能促进社会进步。
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