In this reading list, we want to look at the communication methods think tanks use to bring science into politics.
Professional providers of science communication–whether embedded in research institutions, as companies such as Oikoplus, or think tanks–aim to communicate research results clearly and transparently and make knowledge available for public debate. The target audience for this is diverse. One relevant target group that is usually among the declared addressees of science communication is political decision-makers. In this Reading List, we therefore want to focus on communication methods aimed at policymakers and take a look at think tanks.
Policy oriented think tank work, as stated by Annapoorna Ravichander results in ‘sets of guidelines to help achieve outcomes in a reasonable manner’. They are different from processes and actions. Policies are broad and set a certain direction. While science communication may not have a direct policymaking ambition, it can play a significant role in shaping policy debates, informing decision makers and influencing the development of ideas. And there are methods which can be applied in order to achieve policy influence.
This text hopefully serves as a good introduction to the question of what can be learned from think tanks when it comes to achieving political impact through science communication. And this leads almost inevitably to the question of how to measure the impact of research in the first place. Fortunately, we have already dealt with this in other Readings Lists, e.g here.
What can we learn from science communication? A reading list based on the experiences of the first five years of Oikoplus.
Relevant target groups may be small.
The success of communication is often measured in reach. Reach is also a hard currency in communication for research and innovation projects. However, science dissemination is often very specific, and it’s small target groups that are particularly relevant for successful project communication. In our Domino-E project, for example, one of the most relevant target groups is the small group of people involved in programming satellite missions for earth observation purposes. This target group is not only small, but it is also not easy to identify the communication channels through which it can be reached. However, the content for this target group is specific enough to be able to assume that the target group will find the relevant content as long as it is easy to find. So we decided to use YouTube as a channel.
Simplifying does not have to mean trivializing.
The closer you zoom in on a topic, the bigger it becomes. Many topics and issues appear straightforward at first glance, and only on closer inspection do their complexity, depth and multi-layered nature become apparent. Nevertheless, it is not wrong to take a superficial look at a topic first and only delve deeper in the second step. For experts who are extremely well-versed in a particular subject area, it is often difficult to allow this superficial view. They are too aware of the aspects that only become apparent on closer inspection. And that’s why the superficial view feels like a simplification to them, and often like a trivialization. It is important to allow simplification. But it should be correct. Our REACT project, which deals with the control of pest insect species, can be summarized easily: Insects are sterilized so that they can mate with wild-type insects in the wild without producing offspring. The insect population shrinks in the medium term due to the lack of offspring. In this way, agriculture is protected from the pest. Technically, this method involves a great deal of effort. Nevertheless, we have tried to explain the project in as simple and understandable terms as possible.
The “general public” does hardly exist.
Science communication aims to make research accessible to the general public. This broad public can therefore be found as a target group in the applications and descriptions of many research and innovation projects. However, from a communication perspective, the general public hardly exists. Addressing the public as a whole is damn difficult, or rather: it is impossible. Developing key messages and storytelling approaches automatically involves a selection of target groups. Not everyone finds everything interesting. And if you manage to meet the interests of as many different target groups as possible, that’s already a great communication success. To gain an understanding of how diverse the target groups of our communication in research and innovation projects can be, we have our project partners develop personas in interactive workshops at the start of a project. These are fictitious people who we then use to jointly consider what needs to be done to reach them through our project communication: with which messages, on which channels, when, why, and with what goal in mind? It usually becomes clear quite quickly that the general public is only an auxiliary term that indicates that each project can address many different target groups.
Never underestimate how exciting any topic can be.
How interesting a topic is sometimes isn’t obvious at first glance. No wonder: not every topic can be perceived as equally exciting, and it always depends on how a topic is presented. You could say that it is the job of science communicators like Oikoplus to ensure that a topic arouses the interest of as many people as possible. That is true. But even those who do science communication, first have to find their very own interest in a topic. This does not always happen straight away, which is why it is part of our work to actively seek out approaches to any given topic in which we recognize the potential to tell a story to a specific target group. We therefore force ourselves to be curious and to think empathetically about what the thematic appeal could be for other target groups. Sooner or later, the penny will drop – and then communication will be much easier.
5. Even those who conduct the most exciting research don’t always like to talk about it.
As a journalist, you sometimes have to worm the information you want to convey out of the interviewees. You have to keep asking questions because the interest in conveying information tends to be one-sided. If you’re not doing journalism, but science communication on behalf of science, then this can also happen. This can be surprising, as one would think that the dissemination of information is in the interest of both the scientists and the public and that in the role of the communicator, one only has to do the mediation work. In practice, however, we have often found that researchers sometimes do not always like to talk about their work and that even basic explanations have to be laboriously elicited from them. There is no simple solution to this problem. It is important to build trust, present your communication work as transparently as possible, and create environments in which insights into scientific work are possible. In some cases, this can be a large video shoot in a laboratory with artificial lighting and large camera equipment, and in other cases, it can be a personal one-on-one conversation. In any case, science communication does not happen by itself, even when the most exciting research is communicated.
6. Quality and quantity.
In science, quality is more important than quantity. In communication, this is sometimes not so clear. When the objectives for project communication are laid down in the applications for research projects, the corresponding KPIs are often set high. After all, a proposal submission should express high ambitions. If it is approved, you then realize that the goals may have been set too high and that publications, press releases, website articles, social media postings, photos, videos, and other project dissemination content can be produced, but that it is not easy to maintain your high-quality standards. High-quality content takes time. In our video series for the REACT project, for example, we try to explain the research project as comprehensively as possible and at the same time as clearly as possible. The first of the explanatory videos can be found here. Producing such videos requires a long and detailed exchange with the researchers involved. This is why dozens of such videos cannot be produced in a project like REACT. This should also be expressed in the objectives at the start of the project.
7. Speed is not everything in communication.
Rome wasn’t built in a day. And also, you have to take time in science communication. In other areas of communication, in journalism, PR, and advertising, speed is often a key quality feature. And there are also moments in science communication when it is important to react quickly. But in general, science communication follows the pace of science. For press relations, for example, this means that you can free yourself a little from the temporal logic of media operations. A research topic does not lose its relevance simply because it is no longer news. If, for example, a research paper was published several weeks ago, it is not pointless from the outset to draw journalists’ attention to the paper. This is a major difference between science communication and some other fields of professional communication work.
You don’t have to fully understand what you are communicating.
At Oikoplus, we often benefit from the fact that we approach the research projects that we support in terms of communication as laypeople. The fact that we are not experts in urban development, archaeology, crop protection, satellite technology, or the energy transition has helped us to ask the right questions in the projects that we implement in these areas. After all, the fact that we don’t immediately understand the methods and innovations of our projects is something we have in common with our target groups. This is not to be understood as a hymn to trivialization. Of course, it helps to familiarize yourself with the topics that are being communicated. But you also don’t have to be afraid to bring your expertise, namely communications expertise, to projects that you initially have no idea about. Don’t be afraid of rocket science. Even rocket scientists are sometimes dependent on communication experts.
Think globally, act globally.
To make an abstract topic accessible, it is often linked to a manageable aspect of people’s everyday lives. This is a common method in journalism. To draw attention to the consequences of global climate change, for example, changes to the ecosystem are described at a local level. This creates relatability. We wrote about this in Reading List #010. So far, so useful. In our communication for European and global research projects, we sometimes lack this local or everyday level. We design communication for international target groups – after all, research is international too. The slogan “think globally, act locally” therefore often becomes “think globally, act globally” for us. In concrete terms, this means that science communication cannot always respond to the needs of different local target groups. This is where translations into dozens of different languages and a lack of mobility alone can lead to failure. Science communication takes place on an international level. As a science communicator, you often have to trust that the topics you are communicating about will find their target groups – not the other way around.
10. Curiosity is the best driver of communication.
If you ask us at Oikoplus what drives us, the answer is easy. It is curiosity. In German, the word for it (Neugier) is derived from the greed (Gier) for something new (Neu). We took a critical look at this in one of our last reading lists. We understand curiosity as the constant interest in new experiences, insights, and perspectives. We see it as a great privilege of science communication that we can constantly learn something new in our work, and it even largely consists of this. We enjoy doing it.
In this Oikoplus Reading List we present good reads from the web touching on the question of language in science. Language, understood quite explicitly and rather abstractly.
The favour of the mother tongue
At Oikoplus, the working language in all our projects is English. When we meet contacts in our work with whom we can speak in our native languages (German, Italian, Polish, Romanian), we are always happy. Because honestly, working permanently in foreign languages can be exhausting sometimes. For people working in science and research, it is therefore a great starting advantage if their mother tongue is English. So far, so banal. It is less banal, however, to quantify how great the price is paid by all those whose mother tongue is not English, of all languages. A study by Tatsuya Amano et al. aims to do just that:
„By surveying 908 researchers in environmental sciences, this study estimates and compares the amount of effort required to conduct scientific activities in English between researchers from different countries and, thus, different linguistic and economic backgrounds. Our survey demonstrates that non-native English speakers, especially early in their careers, spend more effort than native English speakers in conducting scientific activities, from reading and writing papers and preparing presentations in English, to disseminating research in multiple languages. Language barriers can also cause them not to attend, or give oral presentations at, international conferences conducted in English.”
Mathematics describes the world in a strictly formal way. That is its essence and its task. The world can be described less formally in narratives and legends. Just as mathematics looks back on thousands of years of history, which, interestingly enough, is better told as a narrative, there are countless legends and narratives that are ancient and whose future is threatened. And this is because the languages in which they are told are at stake of extinction. Alexandra Aikhenvald explores how the loss of linguistic diversity is threatened by the extinction of indigenous languages worldwide, and why the loss of stories, legends and myths that comes with it is a problem.
We hope we have found the right language in this Reading List, and that in our forays through the internet over the last few weeks we have once again uncovered a few articles that not only pique our interest.
Storytelling is considered an effective communication method because it engages narratives, which our brains are specifically wired to understand. Similarly in science communication, storytelling translates complex concepts into accessible and comprehensible ideas. What happens, however, in situations of intense difficulties or emergency, which cause hardships, anxiety and distress? These crisis situations draw us more towards facts that ensure security rather that anecdotes that evoke empathy. This reading list focuses on answering that question by analysing how storytelling can still be an effective strategy to bring relevant information to the general public through looking at crisis situations.
Crisis situations are, however, different. That is because these are stress inducing situations, where our brain becomes more neurotic, hurried, irrational, all of which affect our decision making and attention. Generally in this type of circumstance, it would be logical to say that in stressful situations we are more drawn to quickly accessible and short informative snippets of news rather than extensive narratives. However, is that truly so?
Due to its abundance of formats and styles, storytelling is an effective method of communication in many different situations. This means that even in crisis situations, where our brains, due to hormonal responses, are in a much more agitated state, stories can still transmit important information, facts and figures. More so, instead of bombarding us with news, storytelling engages our senses and leads to a more active and critical response, which has the potential to bring social change.
Many tips have been shared over the past weeks and months. This one is the perfect AI for research, and the other is the perfect AI for editing texts. Ideas for the best prompts for semantics-based generative AIs are flooding Twitter, Reddit, and the like. In this Reading List, we don’t want to give tips on which AI can be used for what. For a reading list, that doesn’t make much sense at the moment, not least because of the fast pace of technological development. We also don’t want to report on how AI can have an impact on science communication. We already did that last summer in Reading List #021. Rather, we have collected a few texts on thoughts about how AI could change science in the coming years. Enjoy reading!
Artificial intelligence with an overview
One of the biggest challenges of science, regardless of discipline, is keeping up with the flood of articles. 70,000 publications deal with the protein p53, according to the think tank Enago. This is the first I’ve heard of it today. Apparently, it is relevant for the early detection of tumors. In 1993, it was voted “Molecule of the Year”. On the occasion of this anniversary, an AI of my choice finds the following review: “The first 30 years of p53: growing ever more complex” by Arnold J Levine and Moshe Oren (paywall). In fact, there are now a number of tools that claim to find articles and present them in their respective publication context. The start has been made.
Disruptive Artificial Intelligence
With the newly gained overview, the quality of results and outcomes can also be reclassified. And this also applies outside of science. In an interview with Digitale Welt, Prof. Mario Trapp, director of the Fraunhofer Institute for Cognitive Systems IKS, remarks: “Even if you can still have the results of AI checked for plausibility by doctors today, this will hardly be possible in the future because of the increasing complexity.” The choice of words is exciting: Trained people can still check the plausibility of results. This will probably no longer be possible for a long time.
At that time, Bischofberger concluded that we might soon no longer “react” but proactively take care of ourselves. Five years later, knowledge production could soon be taken proactively into the hands of AIs. The question is whether an objective understanding of science will play into our hands. We will see.
It can be argued well and lengthy about what is appropriate when it comes to evaluating the relevance, quality and significance of research work and making it measurable. The selected good reads encompass a range of perspectives, including open access repositories, research impact assessment, research evaluation projects, comprehensive assessment methods, and research grant evaluation.
For once, let’s not start with theory work, but in a very practical way. The “Your Impact” research guide by the University of Illinois at Chicago (UIC) offers comprehensive information on evaluating research impact. It covers various metrics, tools, and methodologies to assess the societal, academic, and economic impacts of research. This guide provides practical advice to researchers, librarians, and administrators on navigating the complex landscape of research evaluation, empowering them to demonstrate the value and significance of their work.
Choose your methods wisely – they might be assessed
Of course, the choice of method always influences the results. And this also applies to the methods used to measure the impact of science. A recent project on evaluating research conducted by RAND Europe aims to improve understanding and methodologies for assessing research quality and impact. Their website offers insights into ongoing projects, publications, and tools related to research evaluation. RAND Europe’s expertise in research evaluation provides valuable insights for policymakers, funding agencies, and research institutions seeking to enhance evaluation practices and inform evidence-based decision-making.
If you are looking for a clear and theoretically sound introduction to the topic of research evaluation, Evaluating Research in Context: A Method for Comprehensive Assessment by Jack Spaapen, Huub Dijstelbloem and Frank Wamelink from 2007 is recommended. The focus is on one thing, as the title suggests: Context. The right context is important if not only publications in journals and their ranking values are to be counted. Contextual consideration is crucial in science impact assessment. Research takes place within diverse fields, each with its own objectives, methodologies, and timelines. Therefore, relying solely on universal indicators may oversimplify the evaluation process and fail to capture the nuances of different disciplines. By accounting for the contextual aspects, such as field-specific metrics, geographic factors, and research goals, a more accurate assessment of impact can be achieved.
Assessment of research should recognise diversity of outputs, practices and activities
Science impact assessment is essential for evaluating the broader influence and value of research.
When it comes to evaluation and measurability, it is obvious to operationalize success in numbers. However, there is no scheme for this operationalization that can represent the different types of scientific practice in a comparable way. Researchers are aware of this. One answer to the problem is the Coalition for Advancing Research Assessment (CoARA). Hundreds of universities, institutes, and scientific institutions have already joined the Coalition, united by the vision “that the assessment of research, researchers and research organisations recognises the diverse outputs, practices and activities that maximise the quality and impact of research. This requires basing assessment primarily on qualitative judgement, for which peer review is central, supported by responsible use of quantitative indicators.”
Research assessment should always consider the indicators used and the specific context of the research being assessed. By adopting a comprehensive and contextual approach to impact assessment, stakeholders can gain a more nuanced understanding of research outcomes, encourage diverse research pathways, and make informed decisions to support the advancement of science and its positive societal impact.
The ability to understand one’s immediate surroundings has always been an extremely important skill. For this reason, humanity has spent thousands of years developing and perfecting the craft of representing spatial information including routes or landforms. In today’s age of modern technology, however, the amount and variety of information that needs to be mapped are increasing. Nowadays the ability to have a grasp on our surroundings is proving more complex. This reading list will therefore explore how cartography turns out to be useful to facilitate knowledge exchanges and how it can serve as a vehicle for critical thinking.
Empowering citizens to make informed decisions can also have another effect, namely mutual information exchange. Originally cartographers collect data from various measuring tools such as aerial photographs, remote sensing, field observations, or coordinate lists. This data, however, as mentioned by Horizon 2020-funded WeObserve, has a scarce update date due to increased costs and timely data validation procedures. Today, considering the increased complexity of data, cartographers also turn to alternative sources such as citizens.
According to Caroline Anstey for The New York Times, this new shift towards crowdsourcing information is immensely useful to cartography. Citizens provide both quantitative, but also qualitative data often omitted by cartographers. The citizens’ expertise comes from living in one place for a prolonged period of time. Changes in demographics, environment, human relations, or even housing habits are useful to mapping projects as they can translate into policies or planning decisions. To build trust underlying this exchange, cartographers should provide citizens with clear and understandable information.
Obtaining accurate cartographic data through crowdsourcing is something that is in its early stages, but is increasingly practiced. Especially because now citizens have increasingly more opportunities to use tools, which give them access to global data. On an entrepreneurial scale, this is already taking place. The Domino-E project, which focuses on developing a federation layer optimising the availability of Earth observation data, builds on interoperability and knowledge sharing. Knowledge sharing generates knowledge creation, which is why it is important for cartographers to bet for information exchange as it benefits both them and citizens equally.
On difficult topics, moral questions, research ethics and conflicts of interest in science communication.
In science, there are subject areas that are teeming with communication pitfalls. Topics that are controversial in society, research that uses controversial methods and technologies with uncertain consequences. They require sensitivity and caution when it comes to communicating their results in an understandable and accessible way to a large and public audience. Ethical questions are often the subject of intense debate, because widespread social values and morals are challenged. Examples of such research topics are genetic engineering, animal experiments in the life sciences or aspects of gender studies in humanities.
A researcher involved in one of the projects in which Oikoplus is a partner responsible for science communication and dissemination expressed this in an email just recently: „Our research requires that we are very careful with the information that is out there. I would like to avoid a situation of messaging getting misunderstood or misexplained. I could think of a gazillion ways this could go wrong in a spur of the moment.” Well – it’s hard to completely rule out the possibility of communication being misunderstood.
Cutting through discursive pitfalls is not easy. Sometimes it is simply impossible. But transparency and openness, can hardly hurt to enable the broadest and most open discussion about research and its results. At Oikoplus, we support researchers in explaining their work and making it accessible. We always advise them not to hide in the process.
With the current environmental and political climate, the media’s occupation with the topic of energy transition has become more prevalent than ever. Although many news outlets succeed in giving a well rounded and balanced debate on the role of governments, private companies and policies, still very little space is given to exercising the thought of citizen-led efforts for autonomous and local energy control.
Hearing concepts such as sovereign, citizen-led or equal citizen participation within the complex world of energy production can often sound like empty or futuristic phrases, which have no ground in real life. That is understandable, considering the little media coverage citizen-led efforts get, however it is not true. This paper, by students from business management and environmental studies, shines a light on the concept of energy communities, which are based on a collaboration between citizens, governments and businesses for a clean energy transition. Even though these initiatives are not so popularized, they are, as pointed out by Sara Giovanni from Energy Cities a European learning community for future-proof cities, making a great contribution to fight climate change. It is therefore important that the communication and information flow outlets about these organisations are improved and this is what this reading list will be focusing on.
Turning to the external
Some of the prominent issues within the process of promotion of energy communities is first of the lack of easy access to information, which means a need for an active search, which is difficult without having any prior knowledge. Another problem, as pointed out by Wahlund and Palm from Lund University, is the bias towards a decentralized energy model and an underrepresentation of energy communities (EC’s) within the mainstream media. What follows, as presented by the results of this study from two Universities in the Netherlands, is the lack of trust of the wider public towards EC’s and thus an indifference towards taking an active role in energy transition.
On the brighter side, however, for those who already have the sprouts of interest towards EC’s there are various sources including this repository from European Federation for Agencies and Regions for Energy and Environment, which is aimed to give an insight into not only the examples but also various publications and updates related to Energy Communities. Another, a more general example of an informative database is the Projects for Public Spaces website, which brings together a wide array of community led projects from all over the world.
Turning to the internal
One of the benefits that internal communication within energy communities have is the already existing interest in active participation within energy transition, which acts as a drive to seek out and create new knowledge sharing opportunities. This has resulted, as presented by this research paper from the University of Bologna, in quite a large number of attempts being made in order to create EC’s and improve the communication between them. Many studies, like this one, have also been conducted in order to analyse new methods of knowledge sharing within the energy industry and changes, which can be made to adjust the sector to 21st century standards.
According to John S. Edwards from Aston University in Birmingham, however, what renewable energy communities still lack is a good grasp on knowledge management and knowledge distribution, which is very well developed in the oil and gas sectors, causing green energy promotion and internal knowledge exchange to lag behind the fossil fuel industry. The acquisition, archiving and use of knowledge within energy communities is, as maintained by William King in his PhD research in Coventry University, much more understood in the commercial branches than within the EC’s, which are still early in their developmental stages. There is additionally, no theoretical framework that would act as a universal manual, which would specify effective knowledge management strategies (including even the language used, glossary of key terms and their applicability to various contexts).
Energy transition is in many aspects still in its early stages, but through improvement of various elements including turning this niche market into a mainstream process through a more easily accessible media coverage can increase the speed with which current traditional and centralized energy systems are transformed into a community led, collaborative effort.
This Reading List is a little different. All text passages in italics were formulated by an AI named Neuroflash and later translated via Deepl.com. Reading tips and some personal thoughts of the curator appear in the last paragraph.
AI in Science Communication
Scientific articles are often dull and difficult to understand. But that doesn’t have to be the case! Thanks to new technologies, such as AI-based software, also scientists can write their articles in an interesting and easy-to-understand way.
In recent years, the role of AI in science has become increasingly clear. Its ability to analyze and process large amounts of data helps researchers understand and process complex topics. While AI is not yet perfect, it has the potential to make lasting improvements to science communication – especially in terms of efficiency and quality. Nevertheless, it is important to know the limits of the technology and not to trust it blindly. Only in this way can we ensure that AI actually supports us and does not replace us.
Examples of the Application of AI in Science Communication
In the communication of science, i.e. in the writing down of processes and results, AI already supports researchers in literature research or in the preparation of abstracts and summaries. AI can also help with the writing of scientific articles. However, it does not take over the complete work but supports the scientist in the research and the structure of the argument. It is important to keep control! The AI formulates self-criticism: for example, that it cannot convey emotions.
Bottom line: Free your Brain – with AI!
With this contribution already, it is clear that AI will soon play an important role in science communication. By using AI-based systems, scientists can publish their research faster and more effectively. Most importantly, AI enables scientists as well as journalists to write interesting and easy-to-understand texts. If we are to believe AI’s self-assessment, it will soon make a significant contribution to ensuring that the science we produce is read and understood by as many people as possible.
Reading Suggestions and Remarks from a Human Being
The AI appears self-confident. And it has every reason to be. In “Tortured Phrases,” Guillaume Cabanac et al. address the increase in AI-generated texts in science, questioning the integrity of the researchers. Less biased, Yolanda Gil asks in the article published in AI Magazine whether AI will soon be able to formulate scientific texts. Her answer: yes – and sooner rather than later. The resulting challenges and mandates for scientists themselves are detailed by Mico Tatalovic in his paper “AI writing bots are about to revolutionize science journalism” for the Journal for Science Communication.
How does it feel to have the Reading List written? It was important to me to intervene as little as possible in the text proposal. While this is less obvious in English, this can be seen in the gender-specific language of the German version. But also in the confidence that the AI brings to the table. How biased is an AI that writes about itself? A lot of it I wouldn’t phrase that way; I’d tone it down. Or be more specific. These are the formulations from which you can guess an AI. Not a flippant formulation, but not a very specific one either. Daring is the imperative, it seems. Don’t worry. In the future, we will write ourselves again.