Department of Political Science, Communication and International Relations, University of Macerata, Macerata, Italy.
Department of Education, Cultural Heritage and Tourism, University of Macerata, Macerata, Italy.
PLoS One. 2019 Sep 5;14(9):e0221933. doi: 10.1371/journal.pone.0221933. eCollection 2019.
Distinguishing certain and uncertain information is of crucial importance both in the scientific field in the strict sense and in the popular scientific domain. In this paper, by adopting an epistemic stance perspective on certainty and uncertainty, and a mixed procedure of analysis, which combines a bottom-up and a top-down approach, we perform a comparative study (both qualitative and quantitative) of the uncertainty linguistic markers (verbs, non-verbs, modal verbs, conditional clauses, uncertain questions, epistemic future) and their scope in three different corpora: a historical corpus of 80 biomedical articles from the British Medical Journal (BMJ) 1840-2007; a corpus of 12 biomedical articles from BMJ 2013, and a contemporary corpus of 12 scientific popular articles from Discover 2013. The variables under observation are time, structure (IMRaD vs no-IMRaD) and genre (scientific vs popular articles). We apply the Generalized Linear Models analysis in order to test whether there are statistically significant differences (1) in the amount of uncertainty among the different corpora, and (2) in the categories of uncertainty markers used by writers. The results of our analysis reveal that (1) in all corpora, the percentages of uncertainty are always much lower than that of certainty; (2) uncertainty progressively diminishes over time in biomedical articles (in conjunction with their structural changes-IMRaD-and to the increase of the BMJ Impact Factor); and (3) uncertainty is slightly higher in scientific popular articles (Discover 2013) as compared to the contemporary corpus of scientific articles (BMJ 2013). Nevertheless, in all corpora, modal verbs are the most used uncertainty markers. These results suggest that not only do scientific writers prefer to communicate their uncertainty with markers of possibility rather than those of subjectivity but also that science journalists prefer using a third-person subject followed by modal verbs rather than a first-person subject followed by mental verbs such as think or believe.
区分确定信息和不确定信息在严格意义上的科学领域和大众科学领域都至关重要。在本文中，我们采用了一种对确定性和不确定性的认识论立场观点，以及一种混合的分析程序，这种程序结合了自下而上和自上而下的方法，对三个不同语料库中的不确定性语言标记（动词、非动词、情态动词、条件从句、不确定问题、认知未来）及其范围进行了比较研究（定性和定量）：一个来自《英国医学杂志》（BMJ）1840-2007 年的 80 篇生物医学文章的历史语料库；一个来自 BMJ 2013 年的 12 篇生物医学文章的语料库，以及一个来自 Discover 2013 年的 12 篇科学通俗文章的当代语料库。观察的变量是时间、结构（IMRaD 与非 IMRaD）和体裁（科学与通俗文章）。我们应用广义线性模型分析来测试不同语料库之间的不确定性数量是否存在统计学上的显著差异（1），以及作者使用的不确定性标记类别是否存在统计学上的显著差异（2）。我们的分析结果表明：（1）在所有语料库中，不确定性的百分比总是远低于确定性的百分比；（2）生物医学文章中的不确定性随着时间的推移而逐渐减少（与它们的结构变化-IMRaD-以及 BMJ 影响因子的增加有关）；（3）与当代科学文章语料库（BMJ 2013）相比，科学通俗文章（Discover 2013）中的不确定性略高。然而，在所有语料库中，情态动词是最常用的不确定性标记。这些结果表明，科学作者不仅更喜欢用可能性的标记而不是主观性的标记来表达他们的不确定性，而且科学记者也更喜欢使用第三人称主语加情态动词的方式，而不是第一人称主语加思维动词（如 think 或 believe）的方式。
