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【分享】阅读inference推断题

近些天按照小安三塞的方法做阅读的分类整理,对Inference题形成了一套自己的方法。大家不妨试一试,经过我的测试正确率提高的还是很可观的。

这个也是抛砖引玉,希望有更好方法的可以交流交流~嘿嘿  废话不多说了!Let's go!

Inference简介:
Inference题,顾名思义,推断。就好比,我前文说到“废话不多说了”,就意味着,以下说的话都不是废话(当然不太严谨,严谨一点的推断是:以下说的废话少)。

方法的核心思想:
Sometimes, the answer to an inference question is obvious or simple. If you cannot think of a reason why an inference answer choice is incorrect, then it is most likely correct.我的方法的核心就是这句话。

Inference认识:
inference题,推断的信息源于文章信息。题目答案往往是文章没有直说的内容,需要一点点的努力,把答案推出来。与logic structure区别的一点是:答案不需要利用选项提供的新信息。

方法前提:
按照小安的方法把supporting idea题进行整理,因为这样做能让大家快速定位原文信息。

方法使用:
逐一排除错误选项(这个方法比较笨,就像楼主本人似的,但在复习时还是理解每个选错的错误原因比较好)。

错误的选项为3个类别:
1.无关选项:文中就没提到任何相关的信息
2.有关选项,信息使用有误:文中有相关信息,但原文信息与选项不一致
3.有关选项,推断有误:
   3.1推得太远,原因是需要引入文章外(我们自己想出)的理由。
   3.2推得太近,原因是选项只是叙述文中的原有内容(也就是没有推断,变成了找细节)。【此类错误很少,往往以其他理由排除ABCD选项后,E虽然推断太近,但仍然是答案】
   3.3推错了,原因是有相关信息,但推倒过程中出错,是干扰项的主要部分,因为乍一看很正确,仔细一看原文推断不出选项。

后记:
1.使用该方法并不一定能所有题都正确,因为选项虽然推断正确,但一些词汇,如all、every等,也有可能让选项错误。在这里就先不列到错误类型里,因为所有题大家都应该注意这些细节问题。

2.正如大家所看到的3.2,这个方法还有bug,因为楼主本人就遇到一道题,排除了其他选项后,剩下的一个选项就是替换了原文的几个词(很多细节题就是替换原文一些词汇),当然也可以理解是一种推断。按道理说,原文的细节不应该是推断题的答案,现在我也没法解释这个问题。这个bug有待修复...

欢迎大家来这讨论~
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献上例题一道OG12-33

原文:
   In 1988 services moved ahead of manufacturing as the main product of the United States economy. But what is meant by “services”? Some economists define a service as something that is produced and consumed simultaneously, for example, a haircut. The broader, classical definition is that a service is an intangible something that cannot be touched or stored. Yet electric utilities can store energy, and computer programmers save information electronically. Thus, the classical definition is hard to sustain.
   The United States government’s definition is more practical: services are the residual category that includes everything that is not agriculture or industry. Under this definition, services includes activities as diverse as engineering and driving a bus. However, besides lacking a strong conceptual framework, this definition fails to recognize the distinction between service industries and service occupations. It categorizes workers based on their company’s final product rather than on the actual work the employees perform. Thus, the many service workers employed by manufacturers— bookkeepers or janitors, for example—would fall under the industrial rather than the services category. Such ambiguities reveal the arbitrariness of this definition and suggest that, although practical for government purposes, it does not accurately reflect the composition of the current United States economy.

选项:
The passage suggests which of the following about service workers in the United States?
(A) The number of service workers may be underestimated by the definition of services used by the government.(正确 文中:the many service workers...很多service工人被算到了industrial category里。所以,数量会被低估)
(B) There were fewer service workers than agricultural workers before 1988.(推远了:文中第一句有1988年服务成为第一大行业,但没有支持信息,推不出service workers和agricultural workers之间谁多谁少)
(C) The number of service workers was almost equal to the number of workers employed in manufacturing until 1988.(推远了 同上)
(D) Most service workers are employed in service occupations rather than in service industries.(推错了/干扰项:貌似正确,并不是more service workers in service occupations than service industries,工人该是什么工作就是什么工作,不是因为定义方法的不同,就使service workers变多了)
(E) Most service workers are employed in occupations where they provide services that do not fall under the classical definition of services(该选项推的没错:classical definition:service workers属于service行业,US definition:service workers属于industrial行业。但是!!most service workers 显然不正确,文中只是说many service workers怎么样,而不是most——ETS你太狡诈了!!楼主一开始A选项没看出underestimated是什么意思,就放过了,算成E了...)

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多谢楼主

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其实,大多数infer类题目感觉跟细节题很接近,追加的一点reasonging大都简单,很容易判断,所以关键还是找定位。。。
难的是少数无法准确定位的infer题,要么两个段落间找,要么全文找,如果文章简单易懂还好,怕的就是碰到科技类或者印第安水权之类的,本来就似是而非,再全文infer。。。
不知楼主有没最新进展,有没更好的方法,探讨下啊

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回复楼上
首先抱歉,前一阵忙着实习,把G耽搁了。现在决定3战,共勉!
我很同意你说的“大多数infer类题目感觉跟细节题很接近,追加的一点reasonging大都简单,很容易判断,所以关键还是找定位”!但你说的问题“少数无法准确定位的infer题”,可能是我总结时的疏忽,总结完OG12,每道infer题目都找到了定位点。
能否给我举个例子??我好研究一下?

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