Rick Davies (Dr), Monitoring and Evaluation Consultant, Cambridge, United Kingdom | UK. Websites: http://www.mande.co.uk and http://richardjdavies.wordpress.com/ | Twitter: @MandE_NEWS | rick.davies@gmail.com Skype: rickjdavies
My initial interest in the relevance of evolutionary theory was specifically in a field known as evolutionary epistemology. In its simplest form, this views the evolutionary process as a type of learning process, one involving the selective acquisition and retention of information, happening at multiple levels of scale. In the context of PhD research, evolutionary epistemology was used as a means of understanding organisational learning within organisations, and more specifically, in the operations of a large NGO in Bangladesh (Davies, 1998). It also helped generate two practical proposals – one being a means of participatory impact monitoring and the other being a participatory approach to the exploration of alternate futures. Both involved a particular social implementation of the evolutionary search algorithm: variation, selection and reproduction. The main intellectual influences here have been Donald Campbell, Gregory Bateson and Daniel Dennet.
The second body of ideas that has taken up my time is network analysis, in its many and varied forms. This seems a practical way of thinking about complexity – a body of thinking that overlaps substantially with evolutionary theory. Most attempts to describe/define what complexity is do so by referring to complex systems as networks of some kind. There is a wide range of methods of describing and measuring network structures that is relatively agnostic in terms of the theories that can be used to interpret that kind of data. One good feature of a network perspective is that it can help connect more abstract thinking about complexity to actual observations and measurements. Some intellectual influences here have been Borgatti, Benkler, Burt., Krebs.
The third body of thinking, which has been of more recent interest, is about the measurement, origins and consequences of diversity. Both evolutionary theory and network analysis can have something to say about diversity. So can other fields that are of interest to me. One of which is known as “collective intelligence” i.e. the study of the circumstances where the behaviour of a group can be more productive (on some measure) than that of the best individual in the group. Some intellectual influences here have been Page, Suroweicki, Wagner
Evaluation Uncertainty 
Reblogged this on Systems Community of Inquiry.
Evolutionary Epistemology: ah, Bateson would be smiling. I like the coupling of EE with network analysis and of NA and diversity. My question here is whether the categories necessary to show diversity in a network is nuanced enough to match with real world diversity.