In his new book, Queering the Asian Diaspora: East and Southeast Asian Sexuality, Identity and Cultural Politics, the University of Nottingham’s Hongwei […]
It’s “the revolution of common sense,” President Donald Trump announced in his second inaugural address. And so it is. The latest installment […]
Sage (the parent of Social Science Space) and Surviving Society’s collaborative podcast series, Social Science for Social Justice, has returned for a […]
Public trust in scientists is vital. It can help us with personal decisions on matters like health and provide evidence-based policymaking to […]
To address research credibility issues, we must reform the role of metrics, rankings, and incentives in universities.
In late October, more than 80 percent of Botswana’s electorate went to the polls and voted out the incumbent government. The unexpected […]
In November, Sage and the Academy of Social Sciences hosted the 2024 Campaign for Social Science Annual Sage Lecture. This year’s talk, […]
In this article, co-authors Desiree Meurs, Marise Born, Yolanda Grift, Maaike Lycklama à Nijeholt, and Joop Schippers offer a sneak peek into the inspiration […]
Michael Burawoy, whose embrace of public sociology and the public at work lead him to describe his influential academic niche as “industrial […]
To address research credibility issues, we must reform the role of metrics, rankings, and incentives in universities.
Drawing on discussions with academics who have oriented their work around public engagement and social impact, Daniel Pearson suggests these academics present an opportunity to rethink the existing structures of reward and recognition in higher education.
A new people has emerged in the digital age, that of ‘internet famous’ celebrities. And that new people has a class of […]
Xenotransplantation is a fascinating subject – for obvious reasons, as it involves transplanting organs or other body parts across species boundaries (in […]
Decisions taken now around how generative AI is used by academics and universities will shape the future of research. Mark Carrigan argues whilst optimistic scenarios are possible, generative AI stands ready to feed into an existing productivity oriented framing of academic work.
