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 […]
If we value contrary opinion on campus, say social psychologist Mark Brandt, it’s important to ask: Where are the conservatives?
On September 27, as part of Social Science Space’s series on academic freedom, three of the contributors to that series – Daniel Nehring, Dylan Kerrigan, and Joanna Williams – participated in an hour-long webinar to discuss some of the issues at the heart of this issue.
As part of our series on academic freedom, Dylan Kerrigan discusses the wider implications of the financialisation of academic knowledge production by considering academic book publishing. He asks if the success of academic books is best measured by economic or non-economic criteria, by its impact on the business sector or its veracity, by ideological myth-making or evidence.
A culture of bad science can evolve as a result of institutional incentives that prioritize simple quantitative metrics as measures of success, argues Paul Smaldino. But, he adds, not all is lost as new initiatives such as open data and replication are making a positive difference.
Two scholars who investigate how the public learns about science and then chooses to trust it (or not) address that question in this hour-long webinar sponsored by the journal ‘Policy Insights from the Behavioral and Brain Sciences’ and its parent organization, the Federation of Associations in Behavioral & Brain Sciences.
Sociologist has studied the dance club scene — think of the lamented Fabric nightclub as a cultural touchstone — for years as a ‘participant observer.’ In this Social Science Bites podcast she talks about the scene’s obvious drug use and the mechanics of doing ethnography at a rave.
n the coming year a 15-member panel created through a new federal law will examine how data, research and evaluation are currently being used in policy and program design, and how they could be.
A new survey shoots down the idea that early-career researchers aresomehow more likely to be digital natives and therefore more apt to conduct computational social science than those whose PhDs were issued more than a decade ago.