Public Communication of Science Scoping Workshop (3)

Public Communication of Science Scoping Workshop (3) === ###### tags: `Scoping Workshops` :::info **Using HackMD** You can add comments to this document by selecting the relevant portion, and then selecting 'comment' in the pop-up box. You do not need to sign-in to leave comments. ::: This document provides an overview of the modules for the Public Communication of Science (PCS) course. When providing feedback, please consider the following points: - Do the proposed modules and topics meet your expectations for what a course on PCS should cover? - Are there are any gaps that need to be addressed? - Are there any foreseeable challlenges with delivering these modules and content in an online setting? **Document Navigation** [toc] ## PCS Modules :::warning **Summary** The COVID-19 pandemic has forced public organisations and research institutions to think carefully about how best to communicate complex statistical and epidemiological information to the public, while also dealing with associated challenges, such as the spread of misinformation or disinformation, and the barriers posed by cognitive biases. Increasingly, researchers are also faced with a need to consider how best to communicate their own results in a responsible manner, and why it is so important to engage the public throughout the research lifecycle. This course will explore these challenges, and more, in order to introduce participants to practical tools to support public engagement and communication. ::: ### 1) Course Introduction #### Overview of the Course In this module we will motivate the need for this course by exploring some of the challenges facing modern, data-driven societies, focusing on the importance of participatory public engagement in scientific researcg, and the challenges that can arise during public communication of science. ### 2) Science and Society #### Responsible Research and Innovation In this module we will look at why researchers ought to engage the public in a responsible manner. Rather than viewing science as a detached, institutional practice, oft-confiend to Universities or research institutes, we will frame scientific research as a socially situated practice, in order to emphasise the need for participatory science and public engagement. In doing so, we seek to create a space for self-reflexivity and acknowledgement of value-laden nature of scientific practice. #### Public Engagement and the Ethics of Discourse There are various modes of communication, including verbal, textual, and visual. Each mode can support a different learning style, facilitating public engagement. However, to fully evaluate which method is best it is vital to first consider the ethics of engaging in dialogue. This module will explore what is meant by an ethics of discourse, and discuss what norms ought to be established to support reasonable dialogue. #### Democratic Deliberation and Citizen Science This module will introduce participants to the topic of citizen science and the idea of democratic deliberation. We will explore the philosophical and ethical underpinnings of these ideas, as well as the instrumental value that they can play in improving the efficacy of scientific practice. :::info **Guest Lecture (Title TBC)** *Professor Lina Dencik, University of Cardiff* Lina Dencik is Professor in Digital Communication and Society at Cardiff's School of Journalism, Media and Culture and Co-Founder/Director of the Data Justice Lab. Her research concerns the interplay between media developments and social and political change, with a particular focus on resistance, governance and the politics of data. ::: ### 3) Understanding Bias #### Social Biases The term 'social bias' can refer to a wide-range of phenomena, such as the disparate treatment of persons based on their identity (race, gender, immigration status, etc.) by individuals, institutions or broader social structures. In this module we will explore how social biases affect scientific practice, and what obligations or duties scientists and teams have to mitigate this impact. #### Cognitive Biases We all fall prey to the affect of cognitive biases in judgement and decision-making, many of which can cause systematic errors in reasoning. For example, as a result of 'confirmation bias' we may inadvertently favour and recall information that supports (or, confirms) one's prior beliefs or hypotheses to the detriment of alternative explanations. In this module we will explore how cognitive biases affect scientific practice, and what can be done to minimise their impact. #### Statistical Biases Researchers and scientists are perhaps most familiar with the range of 'statistical biases', such as 'selection bias' which can lead to imbalanced classes in a data sample. Like social and cognitive biases, there are a wide-range of statistical biases. Rather than attempting to cover them all, we will instead explore a procedural approach for transparently reporting the processes of scientific research and practice, which can help individuals and teams better identify the cascading effects of statistical bias. :::info **Guest Lecture (TBC)** ::: ### 4) Tools to Support Public Communication and Engagement #### The Bias Reflect-List Given the large number of social, cognitive, and statistical biases that exist, it can be challenging and time-consuming to consider them all. Therefore, we will explore a method of reflective deliberation that is grounded in the research practices of data science, in order to help participants identify and evaluate the impact of different biases on their own research. #### Data and Research Governance Novel technologies are rapidly changing the researcher's toolbox. There are now countless platforms and software tools to help individuals and teams gather and analyse data, test hypotheses, collaborate remotely with other researchers, and also disseminate research. These tools can be incredibly valuable for reaching the public, but they also pose a variety of risks. In this module, we will critically explore tools for data and research governance (e.g. tools for reproducibility) and consider ethical issues like 'research waste'. #### Responsible Participation: Public Engagement After the Pandemic In this final module we will reflect on how the new ways of working, as a result of the COVID-19 pandemic have altered how scientific research is conducted. We will look at opportunities for novel forms of public engagement, and also speculate about future ways of working.