Number Soup: Case Studies of Quantitatively Dense News
Number Soup: Case Studies of Quantitatively Dense News
复制标题
Number Soup：定量密集新闻案例研究
DOI：
10.1080/17512786.2022.2099954
复制
发表时间：
2022
影响因子：
2.1
通讯作者：
Fraser, John
中科院分区：
文献类型：
--
作者：
Barchas-Lichtenstein, Jena;Voiklis, John;Attaway, Bennett;Santhanam, Laura;Parson, Patti;Thomas, Uduak Grace;Isaacs-Thomas, Isabella;Ishwar, Shivani;Fraser, John
数字本身并不能说明问题--然而，把数字视为理所当然（数字主义）却很普遍。事实上，记者经常严重依赖数字，正是因为它们被广泛认为是客观的。作为一个由记者和社会科学家组成的团队，我们对数量特别密集的从句和整个新闻报道进行了定性探索。密集的从句通常语法复杂，并假定熟悉复杂的概念。它们很少与数据收集方法的解释联系在一起。与此同时，密集的新闻报道都是关于经济或健康的话题，主要是对正在发生的事件的简短更新（例如，股票市场波动; COVID-19病例）。我们建议记者可以通过以下方式支持公众理解：提供更多关于研究方法的细节;撰写更短、更清晰的句子;提供统计数据背后的背景;对不确定性保持透明;以及指出共识所在。我们还鼓励新闻机构考虑结构性变革，如重新思考与新闻通讯社的关系，并与统计学家密切合作。
Numbers don’t speak for themselves – yet taking numbers for granted (numerism) is widespread. In fact, journalists often rely heavily on numbers precisely because they are widely considered objective. As a team of journalists and social scientists, we undertook a qualitative exploration of clauses and entire news reports that are particularly quantitatively dense. The dense clauses were often grammatically complex and assumed familiarity with sophisticated concepts. They were rarely associated with explanations of data collection methods. Meanwhile, the dense news reports were all about economy or health topics, chiefly brief updates on an ongoing event (e.g., stock market fluctuations; COVID-19 cases). We suggest that journalists can support public understanding by:Providing more detail about research methods;Writing shorter, clearer sentences;Providing context behind statistics;Being transparent about uncertainty; andIndicating where consensus lies.We also encourage news organizations to consider structural changes like rethinking their relationship with newswires and working closely with statisticians.
登录
查看更多内容
关于数学的更好消息：研究议程
影响因子：
--
作者：
Barchas-Lichtenstein, Jena;Voiklis, John;Santhanam, Laura;Akpan, Nsikan;Ishwar, Shivani;Attaway, Elizabeth;Parson, Patti;Fraser, John
通讯作者：
Fraser, John
影响因子：
9
作者：
Hinnant, Amanda;Len-Rios, Maria E.
通讯作者：
Len-Rios, Maria E.
新闻和新闻教育中数据和统计的现状：问题和辩论
影响因子：
2.9
作者：
An Nguyen;J. Lugo
通讯作者：
J. Lugo
颠覆主流话语：成人算术社会实践理论（重新）导论
影响因子：
--
作者：
Helen M. Oughton
通讯作者：
Helen M. Oughton
数据新闻、公正性和统计声明
影响因子：
2.1
作者：
Stephen Cushion;Justin Lewis;R. Callaghan
通讯作者：
R. Callaghan