A new report produced by the Digital Science team explores the types of evidence used to demonstrate impact in REF2014 and pulls together guidance from leading professionals on good practice.
In the past few years there has been an insidious rise in predatory journals and publishers, notes Adele Thomas, and African academics have not been immune to their predation.
The content of scholarly debates is increasingly secondary to the instrumentalization of scholarship in the promotion of one’s brand,” says our Daniel Nehring. It may not matter much that this brand is built on — academically at least — somewhat dubious welfare bashing, as long as the right markers of scholarly status are attached to it.
Our goal, say the supporters of the #WomenAlsoKnowStuff database of female political scientists, is to amplify the voices of women in the discipline and in the public eye.
Even as it insists it’s not really saying anything new, the American Statistical Association Board of Directors has laid down a marker in the debate over what constitutes “statistical significance.”
Science and technology systems are routinely monitored and assessed with indicators created to measure the natural sciences in developed countries. Ismael Ràfols and Jordi Molas-Gallart urge the creation of indicators that better reflect research activities and contributions in ‘peripheral’ spaces.
Corporate universities, argues our Daniel Nehring, have come to operate as self-enclosed power structures that are shielded from intellectually driven debate by their authoritarian structures and their anti-intellectual ethos.
Intellectual labor comes to be largely external to the objectives of the bureaucratic regimes that dominate universities, argues our Daniel Nehring, and academics whose careers were built on intellectual labor turn out to be deskilled workers in organizational settings indifferent to their concerns.
An article in the journal Psychological Science, “The New Statistics: Why and How” by La Trobe University’s Geoff Cumming, has proved remarkably popular in the years since and is the third-most cited paper published in a Sage journal in 2013. The idea of an autonomous vehicle – i.e., a self-driving car – isn’t particularly new. Leonardo da Vinci had some ideas he […] Social sciences can also inform the design and creation of ethical frameworks and guidelines for AI development and for deployment into systems. Social scientists can contribute expertise: on data quality, equity, and reliability; on how bias manifests in AI algorithms and decision-making processes; on how AI technologies impact marginalized communities and exacerbate existing inequities; and on topics such as fairness, transparency, privacy, and accountability. If schools provide the proper support and resources, they will help educators move from anxiety to empowerment when integrating AI into the classroom. An article in the journal Psychological Science, “The New Statistics: Why and How” by La Trobe University’s Geoff Cumming, has proved remarkably popular in the years since and is the third-most cited paper published in a Sage journal in 2013. By carefully interrogating the system of economic incentives underlying innovations and how technologies are monetized in practice, we can generate a better understanding of the risks, both economic and technological, nurtured by a market’s structure.
EXPLORE
Impact
Paper Opening Science to the New Statistics Proves Its Import a Decade Later
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A Milestone Dataset on the Road to Self-Driving Cars Proves Highly Popular
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Why Social Science? Because It Can Help Contribute to AI That Benefits Society
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Innovation
AI Upskilling Can and Should Empower Business School Faculty
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Paper Opening Science to the New Statistics Proves Its Import a Decade Later
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To Better Forecast AI, We Need to Learn Where Its Money Is Pointing
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