高考英语模拟试题阅读理解精选编讲第239篇——秒词邦微信小程序

On March 7, 1907, the English statistician Francis Galton published a paper which illustrated what has come to be known as the “wisdom of crowds” effect. The experiment of estimation he conducted showed that in some cases, the average of a large number of independent estimates could be quite accurate.

This effect capitalizes on the fact that when people make errors, those errors aren’t always the same. Some people will tend to overestimate, and some to underestimate. When enough of these errors are averaged together, they cancel each other out, resulting in a more accurate estimate. If people are similar and tend to make the same errors, then their errors won’t cancel each other out. In more technical terms, the wisdom of crowds requires that people’s estimates be independent. If for whatever reasons, people’s errors become correlated or dependent, the accuracy of the estimate will go down.

But a new study led by Joaquin Navajas offered an interesting twist (转折) on this classic phenomenon. The key finding of the study was that when crowds were further divided into smaller groups that were allowed to have a discussion, the averages from these groups were more accurate than those from an equal number of independent individuals. For instance, the average obtained from the estimates of four discussion groups of five was significantly more accurate than the average obtained from 20 independent individuals.

In a follow-up study with 100 university students, the researchers tried to get a better sense of what the group members actually did in their discussion. Did they tend to go with those most confident about their estimates? Did they follow those least willing to change their minds? This happened some of the time, but it wasn’t the dominant response. Most frequently, the groups reported that they “shared arguments and reasoned together”. Somehow, these arguments and reasoning resulted in a global reduction in error. Although the studies led by Navajas have limitations and many questions remain, the potential implications for group discussion and decision-making are enormous.

1907年3月7日，英国统计学家弗朗西斯·加尔顿发表了一篇论文，阐述了所谓的“群体智慧”效应。他进行的估计实验表明，在某些情况下，大量独立估计的平均值可能相当准确。

这种效应利用了这样一个事实，即当人们犯错误时，这些错误并不总是相同的。有些人往往会高估，有些人则会低估。当足够多的这些误差被平均在一起时，它们会相互抵消，从而产生更准确的估计。如果人们相似，往往会犯同样的错误，那么他们的错误不会相互抵消。从更专业的角度来说，群众的智慧要求人们的估计是独立的。如果由于任何原因，人们的错误变得相关或依赖，估计的准确性就会下降。

但Joaquin Navajas领导的一项新研究提供了一个有趣的转折点(转折)关于这一经典现象。这项研究的关键发现是，当人群被进一步划分为允许进行讨论的小组时，这些小组的平均值比同等数量的独立个体的平均值更准确。例如，从四个五人讨论组的估计中获得的平均值明显比从20个独立个体获得的平均值更准确。

在一项针对100名大学生的后续研究中，研究人员试图更好地了解小组成员在讨论中的实际行为。他们是否倾向于选择那些对自己的估计最有信心的人？他们有没有追随那些最不愿意改变主意的人？这种情况有时会发生，但并不是主要的反应。最常见的情况是，这些团体报告说，他们“共同争论，共同推理”。不知何故，这些论点和推理导致了错误的全球减少。尽管Navajas领导的研究有局限性，仍存在许多问题，但对小组讨论和决策的潜在影响是巨大的。

句子成分分析：

This effect capitalizes on the fact (that when people make errors, || those errors aren't [always] the same).

句子语法结构详解：

(aren't = are not)

* capitalizes 为谓语，采用一般现在时。动词采用第三人称单数形式。
* that 为连词，引导同位语从句。
* when 为连词，引导时间状语从句。
* make 为谓语，采用一般现在时。
* those 开头为陈述句。
* are 为系动词作谓语，采用一般现在时。
* the 为定冠词。

句子相关词汇解释：

Vocabulary:

句子成分分析：

Some people will tend [to overestimate, and some tounderestimate].

句子语法结构详解：

* tend 为谓语，采用一般将来时。
* to underestimate 为不定式，作后置定语。
* will 为情态动词。some 为不定代词。

句子相关词汇解释：

Vocabulary:

句子成分分析：

If people are similar and tend tomake the same errors, || [then] their errors won't cancel each other out.

句子语法结构详解：

(won't = will not)

* if 为连词，引导条件状语从句。
* are 为系动词作谓语，采用一般现在时。
* similar 为形容词作表语。
* tend 为谓语。
* to make 为不定式，作状语。
* then 开头为陈述句。
* cancel 为谓语，采用一般将来时。
* out 为副词作宾语补足语(即构成复合宾语)。
* will 为情态动词。their 为形容词型物主代词。each 为相互代词。the 为定冠词。

句子相关词汇解释：

Phrase:

Vocabulary:

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