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How readers understand causal and correlational expressions used in news headlines.

机译:读者如何了解新闻标题中使用的因果和相关表达式。

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摘要

[Correction Notice: An Erratum for this article was reported in Vol 23(1) of Journal of Experimental Psychology: Applied (see record 2016-59631-001). In the article, the fourth author was inadvertently omitted from the advance online version. Also, the second paragraph of the author note should have included the following: “Amy Barrington contributed to the design and data collection for Experiments 2 and 3. We thank the following undergraduate students for contributions to Experiment 1 and pilot work leading up to the project: Laura Benjamin, Cecily Donnelly, Cameron Dunlop, Rebecca Emerson, Rose Fisher, Laura Jones, Olivia Manship, Hannah McCarthy, Naomi Scott, Eliza Walwyn-Jones, Leanne Whelan, and Joe Wilton.” All versions of this article have been corrected.] Science-related news stories can have a profound impact on how the public make decisions. The current study presents 4 experiments that examine how participants understand scientific expressions used in news headlines. The expressions concerned causal and correlational relationships between variables (e.g., “being breast fed makes children behave better”). Participants rated or ranked headlines according to the extent that one variable caused the other. Our results suggest that participants differentiate between 3 distinct categories of relationship: direct cause statements (e.g., “makes,” “increases”), which were interpreted as the most causal; can cause statements (e.g., “can make,” “can increase”); and moderate cause statements (e.g., “might cause,” “linked,” “associated with”), but do not consistently distinguish within the last group despite the logical distinction between cause and association. On the basis of this evidence, we make recommendations for appropriately communicating cause and effect in news headlines. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
机译:[更正通知:《实验心理学杂志:已应用》的第23(1)期报道了本文的勘误(请参阅记录2016-59631-001)。在本文中,无意中从高级在线版本中省略了第四作者。另外,作者注释的第二段应包括以下内容:“艾米·巴灵顿(Amy Barrington)为实验2和3的设计和数据收集做出了贡献。我们感谢以下本科生为实验1和导致该项目的试点工作做出的贡献:劳拉·本杰明(Laura Benjamin),塞西莉·唐纳利(Cecily Donnelly),卡梅隆·邓洛普(Cameron Dunlop),丽贝卡·艾默生(Rebecca Emerson),罗斯·费舍尔(Laus Jones),劳拉·琼斯(Ouravia Manship),汉娜·麦卡锡(Hannah McCarthy),娜奥米·斯科特(Naomi Scott),伊丽莎·沃尔温·琼斯(Eliza Walwyn-Jones),莉安·惠兰(Leanne Whelan)和乔·威尔顿(Joe Wilton)。本文的所有版本均已得到更正。]与科学有关的新闻报道可能会对公众的决策产生深远影响。当前的研究提出了4个实验,检查参与者如何理解新闻头条中使用的科学表达。这些表述涉及变量之间的因果关系和相关关系(例如,“母乳喂养使孩子的表现更好”)。参与者根据一个变量引起另一个变量的程度对标题进行了排名或排名。我们的结果表明,参与者区分了三种不同的关系类别:直接原因陈述(例如,“制造”,“增加”),它们被认为是最有因果关系的;可能引起陈述(例如“可以制造”,“可以增加”);和中等原因陈述(例如,“可能的原因”,“关联的”,“与之相关”),尽管在原因和关联之间存在逻辑上的区别,但在最后一组中并不能始终如一地区分。基于这些证据,我们建议在新闻标题中适当地交流因果关系。 (PsycINFO数据库记录(c)2017 APA,保留所有权利)

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