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2020年GRE考試寫作部分每日一練:Issue題目分享DAY27
幫考網(wǎng)校2020-10-23 11:31
2020年GRE考試寫作部分每日一練:Issue題目分享DAY27

小伙伴們,GRE考試大家復習的怎么樣了呢?下面是幫考網(wǎng)分享的GRE考試作文部分的復習資料,一起來看看吧!

Issue題目分享DAY27

168. "Critical judgment of work in any given field has little value unless it comes from someone who is an expert in that field."

批判性的判斷在任何領域當中都是沒什么用處的,除非它是來自于該領域中的專家。

1. With respect to the social sciences, the social world presents a seamless web of not only anthropogenic but also physical forces, which interact in ways that can be understood only in the context of a variety of disciplines.

2. In contrast, the work of researchers in the purely physical sciences can be judged only by their peers.

統(tǒng)一和分歧之專家

175. "It is always an individual who is the impetus for innovation; the details may be worked out by a team, but true innovation results from the enterprise and unique perception of an individual."

革新的動力往往來自于個人;革新的細節(jié)可能來自于團隊,但是實質的革新都是個人努力和獨特思維的結果。

1. With respect to business innovation, I agree that it is the vision and commitment of key individuals—such as a firm’s founder or chief executive—from which business burgeon and innovative products, services, and marketing and management strategies emerge.

2. Nevertheless, teamwork and individual enterprise are not necessarily inconsistent, as the speaker would have us believe.

182. "It is dangerous to trust only intelligence."

只相信聰明才智是危險的。

Intelligence is sufficient in some cases but not in any case.

1. In scientific studies regarding the physical world, we should depend only on intelligence for discovering and testing truths.

2. However, in the realm of human affairs, we have to use both our intelligence and our hearts to solve problems.

184. "It is a grave mistake to theorize before one has data."

在掌握足夠資料之前建立理論會導致嚴重的錯誤。

1. A theory conjured up without the benefit of data amounts to little more than the theorist’s hopes and desires—what he or she wants to be true and not be true.

2. By theorizing before collecting data the theorist also runs that risk of interpreting that data in a manner which makes it appear to lend more credence to the theory than it actually does.

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