As a precondition to receiving research funds, many research funders require applicants to state how their project will ultimately achieve impacts prior to any work being undertaken. Reflecting on a study of these impact statements made to the Science Foundation Ireland Investigators Programme, Lai Ma, argues that such statements often introduce a narrow short-term bias to considerations of impact and presents four ways impact statements could be used more productively.
Calls to align incentives in academia to promote open research practices are not new. However, in recent years research funders are increasingly implementing policies and schemes designed to promote open science practices amongst researchers. In this post, Maria Cruz and Hans de Jonge outline details of the Dutch Research Council’s (NWO) new Open Science Fund, which they suggest is the natural next step towards a culture of open science in Dutch research.
Forensic psychologist Belinda Winder wants society to understand one key aspect things about pedophilia. “Many people understand pedophilia to be both a sexual attraction to children but also the act of committing abuse against children,” she explains. “And that’s wrong.”
Ellen Hutti and Jenine Harris have quantified the extent to which female authors are represented in assigned course readings. In this blog post, they emphasize that more equal exposure to experts with whom they can identify will better serve our students and foster the growth, diversity and potential of this future workforce. They also present one repository currently being built for readings by underrepresented authors that are Black, Indigenous or people of color.
The use of Amazon’s Mechanical Turk in management research has increased from 6 papers in 2012 to 133 in 2019. Given that the practice is rapidly increasing but scholarly opinions diverge, the Journal of Management commissioned this review and consideration of best practices.
As part of the Impact at UTS podcast series, staff at University of Technology Sydney spoke to researchers about how they navigate collaboration, engagement – with communities, industry and government – and impact.
Biplav Srivastava, professor of computer science at the University of South Carolina, and his team have developed a data-driven tool that helps demonstrate the effect of wearing masks on COVID-19 cases and deaths. His model utilizes a variety of data sources to create alternate scenarios that can tell us “What could have happened?” if a county in the U.S. had a higher or lower rate of mask adherence.