This article explores the evolving phenomenon of science communication in social media and the norms and values that shape these online spaces. We interviewed science communicators on TikTok, one of the most popular social media platforms globally, about using generative AI to produce science-related social media content.

As generative AI applications in science proliferate they prompt a self-reflection on work routines in scientific knowledge production. At the same time, scientific institutions, publishing bodies, and funding agencies are confronted with both regulatory challenges and the task of promoting the use of generative AI in line with good scientific practice.

In this short analysis, Sami Nenno takes a closer look at the content of fact-checks and misinformation in Germany.

The expectation to communicate In 2019, the German Federal Ministry of Education and Research called for a cultural shift toward communicating science (Bundesministerium für Bildung und Forschung, 2019). The former Federal Minister of Education and Research, Anja Karliczek, urged scientists to communicate their research continuously and classified communication as a central task for universities and research organizations (Karliczek, 2020).

In 2019 researchers at Simon Fraser University set out to catalogue the world’s scholarly publishing platforms. They restricted themselves to open source projects, and yet still identified over 50 projects to produce and host scholarly journals and books. The platforms range from established (like Open Journal Systems) to fledgling (like Rebus Ink), and everything in between.

For most liberal democracies, scientific expertise is an important ingredient of political decision-making. Scientific forecasts and assessments of, for example, poverty or social mobility, the impact of exhaust fumes on public health or the risks of viral outbreaks, help governments to weigh arguments and decide on policy measures. But how exactly does scientific knowledge make its way into politics?

Introduction The outbreak of the COVID-19 pandemic led to a global and accelerated digitalisation of all education systems. This quickly revealed many inequalities in access to digital resources and lack of digital skills. What concrete impact has this had on learners and teachers worldwide? How can we address these inequalities in education?

Since the 1990s, health experts have anticipated that we would be hit by an influenza pandemic in the not-too-distant future (cf. Caduff 2015; Lakoff 2008; Weir, Mykhalovskiy 2010). While we may have thought of pandemic primarily in terms of Covid-19 over the past two years, influenza pandemics have long represented the paradigmatic case of pandemic preparedness planning.

In academia, there is a clear understanding of how the quality of research work is assessed. This is done by academic peers in a peer review process. It is only then, through the discourse of expert opinion, that it is possible to determine whether the quality of a paper is good or poor. The peers themselves also determine when science is excellent without using formal criteria or even indicators. Science thus has a monopoly on quality;

***The COVID-19 pandemic experiences of many different countries have shown how an exceptional need for research evidence has led to rapid new deployments of scientists in advisory roles to aid policymakers in making evidence-informed decisions. (1) This has helped us learn how science advisors experience, and try to manage, the challenges of insufficient, evolving, and conflicting evidence as they work to inform public health decision-making.