How do you measure research quality? In the UK, this question is part of a task given to the Research Excellence Framework (REF), a 5-year assessment by expert review of the relative quality of all academic research in the UK.
The REF is a very large undertaking; almost 200,000 separate research outputs and just over 50,000 staff were submitted for assessment with the cost for the whole process at around £60 million. However with the results being used to allocate around £2 billion of funding, the reasoning behind being so thorough becomes very clear.
The methodology of the REF is firmly rooted in the concept of peer-review. Representative expert panels judge entries in each of the 36 different academic fields. Each panel has the responsibility of grading submissions on research output, research impact, and research environment.
However this does not mean that the methods of the REF are necessarily set in stone. The rise in the number and visibility of metrics, alongside the addition of ‘research impact’ as a new area in which entries are judged, has meant that it is being widely suggested that metrics may have a role to play in future iterations of research assessment.
As someone from outside of the ‘scientific community’, it is easy for me to see how the science sphere can be seen as just that – an isolated community separate from the remainder of society. Indeed, in light of Merton & Mulkay’s work (1973 ; 1976), it is explained how science as a discipline is potentially more cohesive than others – all work is cumulative, there are golden rules to which all researchers abide, & there is a good deal of tacit knowledge which is not easily shared or explained to the layperson. Science is truly different from other disciplines – it is arguably the only area that has the potential to get everybody reading off the same hymn sheet. When we look at other disciplines, it is not easy to find the steadfast knowledge that the natural sciences can offer (I will not detract on contentions within science for the sake of argument). I feel it is for this reason exactly that science should be more accessible & less the realm of the white, middle-class male. This stereotype surely perpetuates division & lessens the impact of social good that science has to offer, & further efforts should be made to tackle it. Continue reading
The ideal of diffusion
The 1960s produced a series of economic commentaries on the way in which innovations spread throughout a market. Ranging from Rodgers in 19621 to Bass in 19692 these all developed around the concept of diffusion. Developed formally by Rodgers, and held by many people today, the diffusion theory is a specialised concept of communication. This communication, verbal, nonverbal, and observational, then produces a diffusion curve. What I will attempt to lay out here is a very short critique of the basic theory of diffusion. Unlike most economic commentaries however I will start before the innovation stage and use more recent studies into the sociology of science to examine the nature of scientific investigation and draw parallels to the nature of innovation. When diffusion models are examined in this way they are not only revealed as misleading descriptions of the interaction between firms and consumers, but lacking in any real explanatory power. I suggest instead that a translation model would be far more effective at both explaining the spread of innovations and offering advice towards more effective interactions between firms and markets in the future.
Hello! This is a blog set up by the student community in the Science Policy Research Unit at the University of Sussex. We will regularly be posting comment and criticism on ideas, issues and developments in science and technology policy, innovation, sustainability and anything else that comes under SPRU’s wide umbrella. Simon