Researchers decided to conduct behavioral testing on competition and the process of peer review. What they learned offers some prescriptions for improving peer review going forward.
Sorting music by genre often says more about the sorter than it does about the tune. A new system developed by an interdisciplinary team has come up with a three-dimension test for determining what someone will like apart from the label.
The more brazen the willingness to commit academic fraud, the harder it becomes to prevent, suggests Ian Freckelton. So while there is a role for codes of conduct or even criminal courts, finding ways to push temptation to deceive even further out of mind will likeley prove even more successful.
Universities need faculty who are dedicated to teaching, but the most persuasive argument in support of tenure – its role in protecting academic freedom– has come to be too narrowly associated with research.
Anthropologists use ethnographic methods designed to facilitate their competency in another culture to understand what people do, think, feel and say that might seem strange to an outsider but are completely familiar to an insider. But what does that mean in practice?
There is a modern-day notion that competition will solve all problems, says Rajani Naidoo, and higher education can get trapped in a kind of magical thinking that makes a fetish out of competition.
A new survey in England examines the career outcomes of recent university leavers. For maximum pay, it helps to be a student of economics — and to be male.
As governments seek practical metrics for determining if their research funding is money wisely spent, the quest for ‘impact’ takes on great importance. Drawing from the Australian experience, Stephen Taylor addresses several key measurement principles.
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.
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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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