Translating science for young people

为年轻人翻译科学

基本信息

批准号：
AH/M003809/1
负责人：
Alice Deignan
金额：
$ 18.26万
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FM003809%2F1
关键词：
Translating science young people

项目摘要

The project is concerned with how state-of-the-art scientific knowledge is translated, or, possibly, not translated or mistranslated, in texts accessed by young people aged 11-16. The research focusses on texts produced around climate change, a socioscientific issue of central importance, and one which has implications for lifestyle and patterns of consumption. Understanding such socioscientific issues is central to young people's future lives as active citizens, but 11- to 16-year-olds are unlikely to be able to read the texts in which scientists communicate their research findings, such as articles in specialised journals. Rather, young people find out about scientific issues from a variety of educational and popular texts, as well as from online sources and social media. The translation of information across genres may result in distortion; for instance, there is some evidence that public understanding of the human role in climate change is significantly at odds with the current scientific consensus.To investigate translation in this context, we will conduct linguistic analyses of three large language datasets, composed of collections of texts about climate change, representing the following:(1) the language of science used by experts, represented by research articles and policy texts such as produced by the Intergovernmental Panel on Climate Change;(2) the language of texts that young people access, represented by popular and educational materials, including curriculum materials, educational websites such as 'BBC Bite-size', popular science texts, internet forums, Twitter feeds and other texts used by young people. The selection will informed by interviews with young people and with teachers.(3) the language used by young people interviewed about climate change.We will analyse a group of linguistic devices including metaphors, metonyms, words combinations (collocations) and the use of technical terms. These have been shown to be important in communicating scientific information and stance towards ideas. They can also convey emotional attitudes towards what they refer to, and degrees of probability and certainty. We will compare the analyses of the three datasets and identify commonalities and divergences in what is communicated and how. By analysing the interviews with young people, we will also consider how scientific information, attitudes and probabilities are understood and reframed by the young people themselves. We will use the techniques of corpus linguistics, that is, the use of specialised software for studying large quantities of text automatically, supported by some qualitative manual language analysis. Our procedure is as follows:We will use corpus linguistic software to perform preliminary analyses on the datasets. These techniques will enable us to identify significant quantitative features of the datasets, and differences in language use between them. For instance, we will be able to identify which words are used most frequently in each, and to compare these, and which combinations of words and semantic fields occur frequently in each dataset, and frequently relative to each other. We will also perform detailed manual text analysis of samples of each dataset to identify key linguistic characteristics. This information will be used as a starting point for more detailed language analysis. Corpus software will then be used to study language patterns in more detail, to determine key patterns of meaning and use in each corpus, and differences between them. This use of detailed linguistic methods in tackling young people's understanding of socioscientific issues is innovative.Our findings will be important for professionals concerned with communicating science to the general public, especially young people, including scientists and science journalists. They will also be important for science education professionals, and for organisations concerned with public awareness of climate science.

该项目关注的是如何在 11 至 16 岁的年轻人接触的文本中翻译最先进的科学知识，或者可能未翻译或误译。这项研究的重点是围绕气候变化产生的文本，气候变化是一个至关重要的社会科学问题，对生活方式和消费模式有影响。了解此类社会科学问题对于年轻人未来作为积极公民的生活至关重要，但 11 至 16 岁的孩子不太可能阅读科学家交流其研究成果的文本，例如专业期刊上的文章。相反，年轻人从各种教育和流行文本以及在线资源和社交媒体中了解科学问题。跨流派的信息翻译可能会导致失真；例如，有一些证据表明，公众对人类在气候变化中的作用的理解与当前的科学共识明显不一致。为了研究这种情况下的翻译，我们将对三个由文本集合组成的大型语言数据集进行语言分析关于气候变化的语言，代表如下：（1）专家使用的科学语言，以研究文章和政策文本为代表，例如政府间气候变化专门委员会编写的文章和政策文本；（2）年轻人接触到的文本语言，以研究文章和政策文本为代表。通过流行和教育材料，包括课程材料，教育网站，如“BBC Bit-size”、科普文本、互联网论坛、Twitter 提要和年轻人使用的其他文本。选择将通过对年轻人和教师的采访来确定。（3）接受采访的年轻人关于气候变化所使用的语言。我们将分析一组语言手段，包括隐喻、转喻、词语组合（搭配）以及技术的使用。条款。事实证明，这些对于传播科学信息和思想立场非常重要。它们还可以传达对其所指内容的情感态度，以及概率和确定性的程度。我们将比较三个数据集的分析，并确定沟通内容和方式的共性和分歧。通过分析对年轻人的采访，我们还将考虑年轻人自己如何理解和重构科学信息、态度和概率。我们将使用语料库语言学技术，即使用专门的软件自动研究大量文本，并辅以一些定性的手动语言分析。我们的流程如下：我们将使用语料库语言软件对数据集进行初步分析。这些技术将使我们能够识别数据集的重要定量特征以及它们之间语言使用的差异。例如，我们将能够识别每个数据集中哪些单词最常使用，并进行比较，以及单词和语义字段的哪些组合在每个数据集中频繁出现，并且经常相互关联。我们还将对每个数据集的样本进行详细的手动文本分析，以识别关键的语言特征。该信息将用作更详细的语言分析的起点。然后，语料库软件将用于更详细地研究语言模式，以确定每个语料库中含义和使用的关键模式以及它们之间的差异。这种使用详细的语言方法来解决年轻人对社会科学问题的理解是创新的。我们的研究结果对于致力于向公众，特别是年轻人，包括科学家和科学记者传播科学的专业人士来说非常重要。它们对于科学教育专业人员以及关注公众气候科学意识的组织也很重要。