Social, Behavioral Scientists Eligible to Apply for NSF S-STEM Grants
Solicitations are now being sought for the National Science Foundation’s Scholarships in Science, Technology, Engineering, and Mathematics program, and in an unheralded […]
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.
Below are some of the comments and articles that have addressed the issues of academic freedom as written about in the series appearing at Social Science Space.
Craig Brandist compares aspects of British higher education to the old Soviet Union, with a similar tendency towards stagnation and strategies that workers adopt to absorb managerial pressure.
The American presidential campaign season, official and unofficial, seems essentially endless. But as the US enters the homestretch for 2016, Howard Silver wonders how much all this sound and fury really matters to voters
We often use the metaphor of a war to describe the human struggle against disease. This is a very unhelpful way of thinking, because it generates the sort of hubris exemplified by the Chan Zuckerberg program.
We likely all remember the maxim about statistics and lies. Statistical data do not allow for lies so much as semantic manipulation, explains Jonathan Goodman. In short, numbers drive the misuse of words.
Addressing the consequences of the “prolonged period of uncertainty” in the three months since the Brexit vote, the Academy of Social Sciences and Campaign for Social Science recommend immediate steps the government should take to support UK science and ensure the “long-term health of research is kept to the fore” during the negotiation process.
Novel breakthroughs in research can have a dramatic impact on scientific discovery but face some distinct disadvantages in getting wider recognition and are often cited as a plus in getting published. But new findings suggest an inherent bias in bibliometric measures against novel research.