时间:2019-01-17 作者:英语课 分类:2018年NPR美国国家公共电台7月


英语课

 


NOEL KING, HOST:


Insurance companies and data brokers 1 are more and more often using your personal information from social media to predict your health care costs. And they are exploring ways to use that data to determine the rates that you will pay. That's the finding of a new investigation 2 by the nonprofit newsroom ProPublica. Joining us now from our New York studio is their reporter Marshall Allen.


Good morning, Marshall.


MARSHALL ALLEN: Good morning.


KING: All right - so you found that insurance companies are using stuff that we post on Facebook and Twitter and Instagram. What exactly are they gathering 3?


ALLEN: Well, they're gathering things about your race, your ethnicity, your education level, your TV-watching habits, your marital 4 status, your net worth. They're trying to gather everything they can about us to, in some cases, try and predict what it will cost us to be cared for.


KING: What does me being married or not being married have to do with health insurance?


ALLEN: Well, there's a lot of studies now about social determinants of health - that's kind of the jargon 5 they use to describe it - that show that a lot of a person's health does come from social and economic conditions that they're raised in. And you can kind of see, as a group, how this would happen. So for instance, one of the companies would say, if you're a woman who's recently changed your name, which is something they can tell from public records, maybe you're newly married and so you're about to get pregnant. Or perhaps you are recently divorced and so you're stressed out. And both of those things could lead to higher health care costs.


KING: They are making a heck of a lot of assumptions here. How accurate is this as a method of predicting how healthy people are or are not?


ALLEN: Well, that's what I kept asking them. You know, I had a lot of conversations with a company called LexisNexis Risk Solutions. They're one of the main data brokers who are trafficking in this kind of information. And what they said they've done is that they've linked the personal attributes that we all have to claims data from our medical care costs. And then they use that to draw inferences, which they say are accurate. Now, they haven't done any studies that are available about this. They don't put out any methodology, so we can't really tell how they're doing it. It is a black box. But they say that it is predictive.


I want to point out one other important detail. I wasn't able to nail down whether they're actually using this information to price our health plans right now for a process called underwriting. They're definitely using it to measure our costs and estimate our costs. But what the insurance industry says they're doing is they're using it for case management so they can offer services to help sick people stay healthier.


KING: OK. So they're saying it is a benevolent 6 move on their part.


ALLEN: That's exactly right. They say that this allows them to offer better services for patients.


KING: Is there an argument here that this is exactly what insurance companies do? They get all the data they can on you, and then they figure out how much of a risk you are. I'm just trying to figure out why this is notable. It sort of seems like insurance companies were destined 7 to do this once they knew they could.


ALLEN: Well, it does seem that way, and I think that's a really reasonable question to ask. And you know, they do need to properly assess the risk of each of us so that they can properly price plans so they can know how much we might cost. I mean, that's an important part of the process.


But one thing is this is happening with no public scrutiny 8. And this is also happening in a way where insurance companies could use the information to discriminate 9. And that's not something I nailed down with my reporting, but I talked to a lot of experts about how insurance companies do what's called cherry-picking. And by that, I mean they will try and find the healthiest, lowest-cost people and offer them health insurance. And they will try and avoid high-cost health conditions so that they don't have more risk. The Affordable 10 Care Act has made it more difficult to blatantly 11 discriminate, but experts say the discrimination still exists and that this type of information could be used for that purpose.


KING: Marshall Allen is a reporter with ProPublica. Marshall, thank you so much for joining us.


ALLEN: Thank you.



n.(股票、外币等)经纪人( broker的名词复数 );中间人;代理商;(订合同的)中人v.做掮客(或中人等)( broker的第三人称单数 );作为权力经纪人进行谈判;以中间人等身份安排…
  • The firm in question was Alsbery & Co., whiskey brokers. 那家公司叫阿尔斯伯里公司,经销威士忌。 来自英汉文学 - 嘉莉妹妹
  • From time to time a telephone would ring in the brokers' offices. 那两排经纪人房间里不时响着叮令的电话。 来自子夜部分
n.调查,调查研究
  • In an investigation,a new fact became known, which told against him.在调查中新发现了一件对他不利的事实。
  • He drew the conclusion by building on his own investigation.他根据自己的调查研究作出结论。
n.集会,聚会,聚集
  • He called on Mr. White to speak at the gathering.他请怀特先生在集会上讲话。
  • He is on the wing gathering material for his novels.他正忙于为他的小说收集资料。
adj.婚姻的,夫妻的
  • Her son had no marital problems.她的儿子没有婚姻问题。
  • I regret getting involved with my daughter's marital problems;all its done is to bring trouble about my ears.我后悔干涉我女儿的婚姻问题, 现在我所做的一切将给我带来无穷的烦恼。
n.术语,行话
  • They will not hear critics with their horrible jargon.他们不愿意听到评论家们那些可怕的行话。
  • It is important not to be overawed by the mathematical jargon.要紧的是不要被数学的术语所吓倒.
adj.仁慈的,乐善好施的
  • His benevolent nature prevented him from refusing any beggar who accosted him.他乐善好施的本性使他不会拒绝走上前向他行乞的任何一个乞丐。
  • He was a benevolent old man and he wouldn't hurt a fly.他是一个仁慈的老人,连只苍蝇都不愿伤害。
adj.命中注定的;(for)以…为目的地的
  • It was destined that they would marry.他们结婚是缘分。
  • The shipment is destined for America.这批货物将运往美国。
n.详细检查,仔细观察
  • His work looks all right,but it will not bear scrutiny.他的工作似乎很好,但是经不起仔细检查。
  • Few wives in their forties can weather such a scrutiny.很少年过四十的妻子经得起这么仔细的观察。
v.区别,辨别,区分;有区别地对待
  • You must learn to discriminate between facts and opinions.你必须学会把事实和看法区分出来。
  • They can discriminate hundreds of colours.他们能分辨上百种颜色。
adj.支付得起的,不太昂贵的
  • The rent for the four-roomed house is affordable.四居室房屋的房租付得起。
  • There are few affordable apartments in big cities.在大城市中没有几所公寓是便宜的。
ad.公开地
  • Safety guidelines had been blatantly ignored. 安全规章被公然置之不顾。
  • They walked grandly through the lobby, blatantly arm in arm, pretending they were not defeated. 他们大大方方地穿过门厅,故意炫耀地挎着胳膊,假装他们没有被打败。
学英语单词
(10) ceiling
air crash
air evaporation sludge test
air shutter lever
Allium paradoxum
Alt Ruppin
American pondweed
amidoxime
analogue instrument
anamorphic release print
ase noise enhancement
bazzs
blast furnace gas engine
bourbon tube
Bous
branched decay
bright red blood
by-product materials
cargo handling space
Centrocestus
coinage ratio
commodity cost depletion
congenital agenesis of testis
continuous soaper
continuous-form
delone
eddy diffusivity of momentum
endocrin(e)
Erath County
eresyl blue
extract blood out of a stone
filk
full oil stopper
full-load stall
furamonum
Gakem
good luck charm
granulomatous mural endocarditis
heyre
Histaphene
hydraulic agitator
intelligence index
intransitivization
jean cauvins
kazakhs
Kurdyum
larg
linguistic data
logical database schema
long-run standards
lunawicz
M. A. L. D.
male ease
mock-
multigroup
narrow heritability
niblicking
oil-water front
opinion former
parage
percentage of desulfurization
pinkus metal
pivot-point screw
pleiotropies
Protem
pseudopeptide
psychological research
rake-out
required volume
resultant force coefficient
row-equivalence
rum and butter toffee
ruvo
RVOTP
Saint Lawrence Seaway
serrate
shibani
side reflected
sijitus
single criterion under certainty
Skarszewy
skip day feeding
slam her
sledloads
sleigh beds
soil deformation
special program indicator (44)
St. & P.
statistic hot spot factor
steady state reactor operation
stop-start switch
summation plural
tail-gates
to put out
twenty four solar terms?
van dorens
verruca peruana
water system
weakly Hermitian scalar product
Western literature
William Christopher Handy
zero phase sequence