The Linguist

24 The Linguist Vol/61 No/1 2022 thelinguist.uberflip.com OPINION & COMMENT down from trees, which freed their arms and allowed them, among other things, to create hand axes for cutting, dismembering and digging. Hunting and gathering require a degree of planning: where will the prey be and when are the trees in season? Our early ancestors could think beyond the here and now. Secondly, shorter arms, the baby's larger skull, and the narrower birth canal (all evolutionary changes) made assistance in childbirth essential. Cooperation, helpfulness, plus a large "language-ready brain" allowed the emergence of a protolanguage of simple gestures and sounds, direct and mimetic in character, probably around 1.5 million years ago in Africa or East Asia. Hierarchical grammar was in place by the time Homo sapiens came into being 200,000 years ago. Subtitled 'How we came to talk', this book is a very well-researched and persuasive work on how evolution shaped pre-human development, and our precursors' role in externalising language and bringing it into the world. There are parallels in it with Jacob Bronowski's The Ascent of Man. I have only two quibbles: references to two philosophers seem perfunctory; and I think that, all things considered, the book could be a little more compact and none the worse for it. Graham Elliott MCIL It is important for language professionals to understand the concept of data literacy, and be able to work with data, as often the material to be translated consists of more than pure text. It might include a summary embedded in a dashboard or a graphic image, which translators need to decode in order to express the author's intention. In addition, many of the tools available to language professionals are based on a collection of data, including translation programs and applications for language teaching. Understanding data can help translators to be more creative and accurate. With fast economic and technological growth, a huge amount of data is produced every day. We are surrounded by data in a wide variety of forms, starting from simple notes, words, numbers and symbols, through raw data coming from a primary sources such as machines, chips and sensors, to videos, voice recordings and images. Independent from the qualitative and quantitative value that it represents, data summarises facts on which we base our choices and decisions. This leads to the core principles of data literacy: knowing if the data is trusted, understanding how to interpret it and knowing how to share it with others so they can include it in their decision-making processes. Many companies and organisations are investing in upskilling their employees and members with the aim of creating a data-driven mindset that will benefit the organisation. However, many still lack these skills because comprehending data involves a variety of competencies, including mathematical and statistical skills, often supported by knowledge of Excel. It is a fact-finding process, so knowing how to formulate the right questions, and recognise what data is relevant, is fundamental to understanding the wider context and drawing meaningful insights. A great example is technical translation. Working on a highly complex technical manual describing the functionality of a machine can present a real challenge. As a translator, your task involves correctly understanding the way the machine works. The best approach would be to watch videos or look at technical drawings, and gain a deeper understanding by asking questions ('How does that part work?', 'What is the functionality of this part?'). This also requires an ability to interpret the data included in the technical specifications. How to share your insights with others is another key aspect of data literacy. We often need to ask ourselves if what we are trying to present visually allows others to understand the findings. Should it be a pie chart, scatter diagram, pure text or a simple image? What would be more appealing? These skills are crucial for linguists in teaching roles. It is not only about the knowledge teachers share with their students, but also the format in which that knowledge is presented and how that correlates with the students' abilities. For instance, for vocabulary exercises, would a flash card with an image or just text be more effective? Data literacy is gaining importance in almost every role in the professional world, but when skills are required that might not be our strength, it can put us in a vulnerable situation. Language professionals can take part in data literacy, presentation and visual analytics classes, with free courses online. Using a variety of tools and programmes for translators and interpreters is also useful in exposing us to information presented in a broad variety of ways. Educational organisations, meanwhile, can incorporate data literacy classes into the curriculum, speak to students about the advantages of being data literate, and present information to students using various formats. Joanna Biernat MCIL linguist.editor@ciol.org.uk Data literacy for linguists Caught reading The Linguist Former CIOL CEO Ann Carlisle sent in this photo of her with our 'cycling' cover during a break from a bike ride. Email linguist.editor@ciol.org.uk to share your snaps. © SHUTTERSTOCK

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