【Native Speaker每日综合训练—40系列】【40-17】文史哲

AceJ

内容： AceJ 编辑：AceJ


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Part I: Speaker

Marrying Young

Irene:  Damon and his  girlfriend just got  engaged.  They’re  planning on getting  married this summer.
Ken:  They’re too young!   Marrying young  poses all kinds of  problems.
Irene:  Such as?
Ken:  Such as the two of  them lacking  maturity.  They may  think it’s fun to play  house right now, but  they’re not prepared to face  the realities and  responsibilities of  matrimony.
Irene:  I think you’re  selling them short.   They’ve been dating for two  years and  there’s no ideal age  for marriage.   
Ken:  Yes, but we all know  that marrying young will  doom them to a life of  regrets.
Irene:  That’s a bit  harsh, don’t you  think?  A lot of people who  marry young have  successful marriages.  I like  the idea of growing  old with your spouse.   You can  reach many of life’s  milestones together.
Ken:  Like reaching the  legal drinking age?
Irene:  Don’t be  facetious.  Getting  married will give them  stability and  someone to lean on.  I think  they’ll be great as a married  couple.
Ken:  Well, I hope they  beat the odds...or at  least learn a lot for their  second  marriages.
         
Source: ESLpod
http://www.eslpod.com/website/show_podcast.php?issue_id=15541111

[Rephrase 1, 17:40]

AceJ

Part II: Speed

How Do You Become Better Politically Educated?

BY Quora Contributor| Aug 21, 2014

[Time 2]
Focus on policy, not personality. A lot of politics is a soap opera: who's popular, who's not, who's misbehaving, who's rising, who's falling. All of that drama matters, but only because of its eventual effects on what actions the government takes and what policies it enacts. For now, the soap opera is noise to you. (And a lot of it is noise, period.) Resist the urge to watch it, and don't let anyone convince you that you're uninformed when you don't. It doesn't matter who the players are until you understand the game.

Start by picking a few topics that you care about or find interesting. These don't need to be the hot issues of the day. They can be broad topics like foreign policy or immigration or narrower topics like music education in public schools. One nice thing about democracy is that you choose what's important to you. There are too many issues for everyone to become experts on all of them, so don't feel bad about what you skip. There are other citizens to pay attention to those topics.

Learn as much as you can about the topics you chose. My recommendations are to stick with nonpartisan sources when possible and to learn as much as you can about a problem before looking at anyone's proposed solutions.
[219 words]

[Time 3]
After enough research on your chosen subjects, you will probably develop opinions on what the government ought to be doing about them. The next step is to learn about the structure of government. Which parts of the government are responsible for making and executing the decisions you care about? Are they the responsibility of your local government, your state government, the federal government, or some combination of those? Is this an issue where the important decisions are made in law or one where an administrative body is the primary player? This part of political literacy isn't exciting to most people, but if you don't understand how the government functions, you end up looking to the wrong people for solutions and blaming the wrong people for failures. The example I always give: Presidential elections are decided mostly based on domestic issues, yet presidential power is mainly in foreign policy. Congress has most of the power in domestic policy, but blame and credit for the laws Congress passes usually goes to presidents (Obamacare, the Bush tax cuts).

Once you've established your views on policy and know who is responsible for them, it's finally time to go back to the soap opera. Now you're equipped to see politics as something more than a popularity contest. You can ask the right questions, look at candidates' platforms, and figure out what it will mean for your chosen issues if a particular candidate wins. You'll notice that some politicians don't know what they're talking about, some are saying whatever they think voters want to hear instead of telling hard truths, and some are well-informed and competent but have values different from yours. Look at the politicians you have to choose from and find the ones who care about the issues you think are important, who have the education or experience to understand those issues, and whose ideas and views on the issues are close to yours. Vote for them.

Go through those steps, and you'll be a more educated voter than most.
[336 words]

Source: Slate
http://www.slate.com/blogs/quora/2014/08/21/how_do_you_become_better_politically_educated.html

Do All Languages Derive from a Single Common Ancestor?

BY Gretchen McCulloch | Aug 21, 2014

[Time 4]
The Tower of Babel story is a fanciful attempt to account for a very real question: What was the first language and why are there now so many of them?
The video below from TED Ed shows a brief history of how languages evolve, as speakers of the same language lose contact with each other in the centuries after migration and gradually drift linguistically in different directions.

What's most interesting is not simply how we got multiple languages but rather how we determine, without the benefit of a time machine, which modern languages are related. To do this, historical linguists compare large numbers of words in different languages, looking for similarities that can't be explained by other factors, such as onomatopoeia (the word for cat is something like "miao" in several languages, but, well, there's likely an obvious reason for that) or borrowing (the word for tea in most languages is something like te or cha, but those can both be traced back to trade routes from different parts of China).
[171 words]

[Time 5]
Similarities that are solid evidence of common ancestry may at first not look like similarities at all. For example, compare the English words father, foot, far, and five with the Ancient Greek words meaning the same thing: pater, podos, per (technically "forward"), and pente. Notice anything? The English terms all begin with an "f" sound while the Ancient Greek ones start with a "p" sound. When you piece together a whole series of systematic parallels like this across several languages (we can add in Latin pedes and German Fu?, both meaning "foot," for example), you can begin figuring out what the common ancestor, known as a proto-language, might have looked like.

The common ancestor of English, Latin, Greek, Russian, Gaelic, Hindi, and many other languages spoken in Europe and India is known as Proto-Indo-European, whereas the more recent common ancestor of just English, German, Dutch, Norwegian and the other Germanic languages is known as Proto-Germanic. The video below describes more of these systematic sound changes between Proto-Germanic and the rest of the Indo-European languages, and how they were discovered by linguists including the Brothers Grimm (yes, those Brothers Grimm). More in the video below.
[194 words]

[Time 6

We can do pretty well going step-by-step with this base-level comparison of languages—whether modern or those for which we only have written records—which has enabled linguists to devise around 50 proto-languages to varying levels of detail. But the real time-machine problem kicks in when we attempt to go even further back, back to what the common ancestor of these proto-languages might have been. Since there aren't any modern human societies that are incapable of language and any baby can learn any language, it's not unreasonable to suppose that we were probably using language when the first genetically modern humans began to spread throughout, and out of, Africa. But unlike cooking utensils or hunting weapons, languages don't leave physical artifacts of being spoken, and writing of any kind wasn't invented until somewhere between 50,000 and 300,000 years later. Ish.

And unfortunately, this means that any theory of the first human language must be based on pretty darn flimsy evidence. This problem was recognized as early as 1866, when the Linguistic Society of Paris prohibited further papers on the topic, and although this ban is no longer heeded, there's still nothing like consensus on where language came from or what the earliest ones might have sounded like.

But one tantalizing piece of evidence comes from a curious source: the newest languages of the world, like Nicaraguan Sign Language and other creoles, which arise when a group of children make order out of inconsistent linguistic input. We may never know for sure, but perhaps the process of creating a new language from scratch hasn't changed that much across the millennia. [269 words]

Source: Slate
http://www.slate.com/blogs/lexicon_valley/2014/08/21/origin_of_languages_tower_of_babel_proto_languages_and_the_brothers_grimm.html

AceJ

Part III: Obstacle

Pandora and the White Male

By Vauhini Vara | Aug 22, 2014

[Paraphrase 7]
On Wednesday, Pandora became the latest Silicon Valley company to publicize a breakdown of its employees by gender and race. Notably, Pandora employs a much larger share of female workers—about forty-nine per cent globally—than most of the other big companies that recently disclosed their numbers, including Google, Apple, Twitter, and Facebook (in all these companies, women only make up around thirty per cent of employees). Pandora also appears to have a larger share of underrepresented minorities than many of the others. The company, commentators concluded from the figures, must be doing something right.

It’s notable that these disclosures no longer come as much of a surprise; not long ago, this kind of information tended to be hidden away in human-resources departments. (Companies of a certain size must report diversity figures to the government, but they don’t have to make them public.) That changed in May, when Laszlo Bock, Google’s senior vice-president of people operations, published a blog post that began, “We’ve always been reluctant to publish numbers about the diversity of our workforce at Google. We now realize we were wrong, and that it’s time to be candid about the issues.”

The figures were startling. As of January, Google’s global workforce was seventy per cent male and thirty per cent female. Sixty-one per cent of workers in the U.S. were white. “Google is miles from where we want to be,” Bock admitted. So, apparently, is much of the rest of Silicon Valley. Google’s disclosure inspired, or perhaps shamed, LinkedIn, Yahoo, Facebook, Twitter, and eBay into following suit, and their numbers don’t look much better.

Observers have noted, though, that there are variations in the statistics. Pandora and eBay, in that order, have shares of female employees that come closer to an even split.

Apple, followed by Pandora, has the biggest share of Hispanic employees, while Apple and eBay have the highest proportion of workers who are black. (Gigaom has a nice breakdown of the numbers.) Some of the coverage of these differences has tended to congratulate companies like Pandora, whose figures look relatively diverse. But to suggest that these firms are doing something right, and that the less diverse ones are doing something wrong, is an oversimplification. I spoke to Hadi Partovi, a veteran entrepreneur and investor in Silicon Valley, who said that the discrepancies seem to stem from the nature of the companies’ employee bases. Across all the companies, tech workers, like software engineers, tend to be disproportionately male, and either white or Asian. At Pandora, for example, eighty-two per cent of global tech workers are male, while eighteen per cent are female—and white or Asian workers make up eighty-eight per cent of its U.S. tech workers. What makes certain companies look much more diverse than others may be that they happen to have fewer tech employees compared with workers in other areas, like marketers or salespeople.

What’s more, from Partovi’s perspective, the astonishing maleness and whiteness of Silicon Valley’s tech workers has less to do with Silicon Valley itself than with the education system that prepares kids to work there—or, more often, doesn’t do so. Women earn about eighteen per cent of computer-science degrees in the U.S. Black and Hispanic students each earn ten per cent or fewer. “If you have a really undiverse student population, it’s hard to make an even more diverse workforce,” Partovi said.

Partovi has co-founded a nonprofit, Code.org, that tries to expand participation in computer science by women and underrepresented people of color. But instead of targeting Silicon Valley companies, or even universities, the organization is focussing on elementary schools, where Partovi believes the problem starts. Most schools don’t teach computer science, and those that do tend to be suburban or private schools that serve children from privileged—and, often, white or Asian—families. What’s worse, those that do teach computer science tend to be high schools, and once kids get to high school they already have preconceived notions about what a computer programmer looks like, which can dissuade students, including girls, who don’t fit that image.

So Code.org is persuading elementary-school teachers to include computer-science classes in their curriculum—for all students, not just the ones who opt in. “If you tell a nineteen-year-old black girl, ‘Do you want to take a computer-science class?,’ they don’t think it’s fun, because society has told them that computer programmers are white males,” he said. “The earlier we start, they have no stereotypes.”

After talking with Partovi, I called Nicki Washington, a black woman who is a professor of computer science at Howard University, a historically black institution, and who has been programming since her childhood in Durham, North Carolina. By way of introduction, she told me, “I would say that my background probably isn’t the norm.” Her mother was a software programmer at I.B.M., and Washington grew up surrounded by black female engineers: “They were my mother’s friends and co-workers.”

Washington said she agreed with Partovi that most kids—especially girls and minorities—aren’t exposed to computer science early enough. But she also feels that tech companies need to be doing far more to recruit women and minority employees. Among tech companies, Microsoft and Google have been particularly aggressive in recruiting from Howard, she said, along with Wall Street firms, particularly Goldman Sachs. But elsewhere, even when students get internships, they often don’t turn into full-time offers—and, in some cases, employers suggest that this is because they don’t fit into the “culture” of the companies.

Corporate culture, with all of its subtle signifiers and codes of conduct, is invariably linked to society’s broader concept of culture—and all its complicated nuances having to do with race and gender. In Silicon Valley, it might seem innocuous, or even meritocratic, for a startup’s software programmers to sit at the top of the social hierarchy—but, when you consider that software programmers, as a group, tend more often to be white and male, this becomes more fraught. Washington told me that her students who intern in Silicon Valley often tell her that they worry about fitting in—not because they don’t know how to code (they do) but because their social lives are different from those of their co-workers. This may seem like a superficial concern until you consider that these differences may well be influencing their managers’ sense of whether they are a good “cultural” fit.

“You feel like you’re spinning your wheels when you’re pushing students to be the best and brightest, and telling them, ‘You need to be competitive,’ but when it’s time to interview, they can’t get jobs—not because they’re not technically sound, but because they don’t fit into the culture,” she told me. “It’s 2014. I expected this when my mother was working at tech companies in the eighties and nineties, but not now.”
[1139 words]

Source: The New Yorker
http://www.newyorker.com/tech/elements/pandora-white-male

小蘑菇开始打怪

占座先~~
----------

speaker:

two young are going to marry

it may be too early for the marriage

there is no specific time for marry

time2:

pick on topics you like

recommendations

time3:

know the government department responsible for the topic

politicians perform bad

time4:

all languages come from one ancestor

how to distinguish

time5:

some examples

p=f

more in video

time6:

no evidence unlike hunting weapons

never for sure

time7:

P, large share of female workers

the info get publicised

more white workers

statistics on male and female workers

the amount of female learn cs is much less than male

fit in the corporate culture

洋沫沫

time2: 2'16
time3:2'47
time4:1'37
time5:1'34
time6:2'49

obstacle: 10'40

引子：pandora employee structure is more diverse than other.
分析：an entrepreneur states, not because...but because education
suggestion: start computer science from elementary school
递进：professor from Howard agree the situation should be changed from elementary school.
新原因：culture adverse impact doesn't change recent decades

slave918

T2 1:30

Focus on the policies but not thecharacters.

Firstly, you need to pick a field which youare interested with and learn as much you you can in this field.

T3 1:54

The next step is find out what part ofgovernment is responsible for your interesting field and understand how itfunctions.

Then you can go back to see the soap operaand decide on your own judgment who are the best candidate.

T4 1:27

Why there are so many languages in thisworld

the scientists are looking for thesimilarities in many languages to find out what determine how we chooselanguages

T5 1:57

Some similarities are not explicit.

how the scientists find out this languagechanges and how they find it.

T6 1：42

since many languages are not written down,scientist cannot make a consensus what's the predecessor of all the languages.

However, recently a new discovery conveysthat the the process of creating a language may not change much across themillennia.

T7 11:52

In P, there are more female and minorityemployees.

Since Google reveals its pattern ofemployees, activating other companies to do the same thing.

In tech companies, like Apple and Ebay,there are more black and Asia.

Maybe, because P is not tech company, sothere are fewer black and asia.

Actually, it is fewer female students intech majority leads to this phenomenon.

Problem:

1.elementary school not offer the tech knowledgeand misguide many female students.

2.tech company should recruit more femaleand minorities.

jfire

time2 00:01:26.9
time3 00:02:10.0
time4 00:01:11.2
time5 00:01:20.8
time6 00:02:00.6
obstacle 00:08:58.8

neverland1021

谢谢aceJ~

[竟然忘记点计时了⊙﹏⊙b汗]Politics is like drama, the good thing is you can choose what to hear. Recommendation: choose the nonpartisan source.
2'32 Know the political structure- whether the specific policy is decided by the local government, the state government or the federal government？Two examples: president is elected through the domestic votes, but president influences the foreign policy most; Congress is responsible for XXX, but president is mistakenly wrong blamed.
After you know the government structure, you may go back to the political soap opera, and investigate the related politian's background to see whether he or she can make the suitable decision that you care.
1'15 Raise the question: whether all languages in the world have the same ancestor? Without the timeframe benefit, two resources:1)XXX Onomatopoeia:2)borrowing.
1'32 similarity from the seemingly dissimilarities between different language. Example: five English words begin with "f"  and five Greek words that have the same meaning begin with "p"
a proto-Language for European language and India language.
2'06 走神了。。。It's impossible... spreadout....Africa...
9'30
Main Idea: the reasons for less diversity in high tech companies (univercities, universities, elementary schools, company culture).
Attitude: netural neutral
Structure: Take an specific company: Pandora is relatively more diverse than other high tech companies in Sillicon silicon Valley.
==> High tech companies used to avoid to reveal figures of diversity to the public, but now they believe they should
==> compare the figures between different companies (race - Asian, Hispanic, Black, white, sex)
==> Oversimplizing the diversity question - less diversity means bad - is not true.
==> Reasons for little diversity: education in universities, sterotypes, stereotypes company culture.

第二遍：
Timer 1: Choose a nonpartisan source possible and learn as much as you can before exposed to a politicians opinions. (补充)
Timer 2: clarify which politician really cares about your question that you think are important.（补充）

cyndichiang

Time2 1'27''
There are so many polictics that  you need not pay your attention on all these issues

Time3 1'52''
Step1: learning the background of the issues you are interested and knowing who are exactly in charge for that,then according to these knowledge establishing your own opinion
Step2: find the right candidate who you will vote  for

Time4 57''
Time5 1'07''
Time6 2'10''
Modern languages are related  or maybe they have a common ancestor,but we haven't figured out yet.

Obstacle: 7'08''
Pandora publicized its distribution of employees: much larger share of female workers
Google and other tech companies only have a small fragment of female and a large number of their employees are white
Reasons: school education
stereotype: the color and female have unrepresentitive images
corporate culture

油桃F

Speaker
M: oppose marrying young, thinks it will cause many problems; W: support. give their stability and someone to lean on

[Time 2] 1'37
Policy is like soap opera and people cannot learn every aspect. The way to learn is to focus on nonpartisan sources.

[Time 3] 2'22
The next step is to learn the structure and function of the government. After that, you can focus on the policy and vote for the right person.

[Time 4] 1'15
The history of language and the relationship among different languages.

[Time 5] 1'24
The common ancestor of languages

[Time 6] 1'58
We still don't understand where the first language comes from.

Obstacle
Many companies in Silicon Valley have disproportionate rate of gender and minority. And some companies looking more diverse is because they have fewer tech workers than other companies.
reasons:
Girls or minorities lack knowledge of computer science and this problem should be solved in elementary-school.
Students worry about corporate culture that doesn't fit for them but all companies culture comply with the society's broader concept of culture.