Could Distributed Peer Review Better Decide Grant Funding?
The landscape of academic grant funding is notoriously competitive and plagued by lengthy, bureaucratic processes, exacerbated by difficulties in finding willing reviewers. Distributed […]
As protests against police violence and racism continue in cities throughout the U.S., the public is learning that several of the officers […]
Countries across the world have been turning to behavioral science in the fight against coronavirus. In May, The New Scientist proclaimed that ‘behavioral science is […]
David Canter considers the social psychological processes that turn emergencies into disasters.
“You don’t have to go back many months,” says Hetan Shah, the chief executive of the British Academy, in this Social Science Bites podcast, “for a period when politicians were relatively dismissive of experts – and then suddenly we’ve seen a shift now to where they’ve moved very close to scientists. And generally that’s a very good thing.”
With climate change disasters, as with infectious diseases, rapid response time and global coordination are of the essence. At this stage in the COVID-19 situation, there are three primary lessons for a climate-changing future: the immense challenge of global coordination during a crisis, the potential for authoritarian emergency responses, and the spiraling danger of compounding shocks.
“Being led by the science” evokes a linear model of policy making which is more a myth than reality. In reality, politicians use claims about scientific knowledge in order to justify a course of action.
Models are not meant to predict the future perfectly – yet they’re still useful. Biomedical mathematician Lester Caudill, who is currently teaching a class focused on COVID-19 and modeling, explains the limitations of models and how to better understand them.
As far back as we have records, humans have tried to predict the future. Some societies turned to prayer, divination or oracles. Others to tarot cards or crystal balls. In the modern world, much of that function is fulfilled by mathematical models. Is this new technology of forecasting really an upgrade?