Social Networks and their Limitations

My research interests, as applied to assessing green innovation, technology, clusters, strategic alliances or policy development, etc. is based upon understanding the social networks that afford the relationships on which these new ideas or innovations emerge. This month I’ll introduce a few academic considerations about social networks, while next month I’ll try to explain how I’m trying to develop a corrective to the limitations that social network thinking needs to solve if it is to be an effective explanation of the interdependencies that it describes.

Attempts to describe and explain the social interactions that support organisations and other social phenomena make use of a variety of models and methods. There are, though, a limited number of paradigms that dominate the literature, and among these, emerging as the market leader, is that of the network. Stephen Borgatti and Pacey Foster illustrate the exponential growth of network-based research outputs with bibliometric data (Borgatti and Foster 2003: 992), arguing that the network paradigm forms part of a more general move “away from individualist, essentialist and atomistic explanations toward more relational, contextual and systemic understandings” (Borgatti and Foster 2003: 991). In this moth’s blog I will briefly examine some of the key features of network theory. The network paradigm does not represent a unified approach to research; network models are themselves diverse but share characteristics and assumptions. The use of such models in addressing the issue of innovation (the theme of this paper) seems a sensible choice as networks are able to capture a sense of the interdependencies of organisations and the channels of exchange that enable the relationships necessary for innovation to develop and be maintained (Freeman 1991). Equally, network descriptions can be applied to a variety of innovation-related phenomena. Examples include Powell, Koput and Smith-Doerr (1996), who use network patterns to describe the growth in corporate partnerships and external collaboration and the purpose such relationships serve, while Bengt-Åke Lundvall, with a very different approach to organisational adaptation, uses network descriptions to exemplify the process of knowledge transfer and learning between different firms (see Lundvall 1992).

Come off it, REF!

The REF could have an influence on how academics engage with non academics

This post isn't about what is happening on various football fields but on different academic fields. The REF in question (Research Excellence Framework) is in many ways an improvement over the previous Research Assessment Exercise (RAE), with 20% of the assessment based upon the impact of research on non academics. There is, however, a catch: the research not only needs to have a justifiable impact but must also be published in academic journals with an impact factor. Departments noted for their excellent work with the general public, policy makers, business people, practitioners will not be credited by the REF unless the research they develop to help such stakeholders is published in journals used almost exclusively by (a small number of) academics. Why is this a problem? My view is that building a field or developing a discipline is not able to develop in an inclusive way if it follows the Kuhnian approach to research termed “normal science” based on past scientific achievements that the appropriate academic community acknowledges as a foundation for its practice. Kuhn describes these achievements, or “paradigms” as both sufficiently unprecedented to attract a group of adherents away from competing modes of academic research, but, at the same time, sufficiently open-ended to leave various problems for the community of research practitioners to address. Paradigms, in this way, thus help academic communities to demarcate their discipline. They do so, Kuhn argues, by creating avenues of inquiry, helping to formulate research questions, directing the selection of methods appropriate to these questions, defining areas of relevance, structuring the fact gathering process and identifying acceptable technologies appropriate for research. A paradigm also acts to draw in individuals to act as advocates. These advocates and followers are then transformed into a research community, a profession or a discipline as the paradigm becomes accepted and gains credibility. This occurs, Kuhn argues, through the formation of journals, societies or specialist groups, which develop the discipline through articles that are directed to their colleagues who accept the paradigm, rather than needing to justify the concepts, questions, and methods from first principles. This professionalism is supported by the community using its expertise to claim, both for themselves and their paradigm, a place in the academic establishment.

The cultural branding of Climate Change campaigns?

Brands are not just efficient communication tools

While the business application of new modes of branding have been explored in detail, the cultural and communication implications are perhaps even more significant and yet remain an under researched area.  Branding is no longer the simple art of product differentiation using a pleasant logo or clever product name.  Since the development of the mass media, branding has become a key driver in the process of the globalisation of product development and promotion strategy, but also the communication of ideas, cultural icons and social movements.  With the integration of ICT, low cost multimedia and extensive knowledge networks, the way in which branding has traditionally been used to promote products has been revolutionised, but the strategies that have supported the added value that we as consumers attribute to the products/services can now be extended to a range of cultural activities and identities as though they were commodities.  Likewise, the sophistication of consumers has meant that successful branding strategies depend upon the ability of a brand to resonate with complex, and shifting, cultural values.  The merging of these two tendencies has meant that cultural branding, and the branding of culture, are now interdependent forces in the social mediascape in which contemporary life is represented and performed.

What is E3MG?

E3MG sounds complicate - it is!

One of the key areas of research that 4CMR is involved with is E3 modelling.  Over the past few years one of the central models, E3MG (Energy-Environment-Economy (E3) Model for the Globe), has been improved as part of a concerted effort by the core research group.  In the near future the improved model will be used to assess policy scenarios related to carbon emissions.  Many of the people who follow this blog will have a vague idea of what such a model is, but this month I will be introducing the model in more detail.  If you are interested in climate change debates but are turned off by the technical details of econometric modelling, then perhaps this month’s blog article is not for you.

OK, so what is E3MG? The model is one of a suite of E3 models maintained and improved by Cambridge Centre for Climate Change Mitigation Research (4CMR) and Cambridge Econometrics under the guidance of Terry Barker.  Each of the models within this suite has a specific territorial focus; E3MG extends coverage across the globe. 

Emissions Reduction Strategies: How to Choose the Right Policy Mix

Policy makers must ensure that the policy mix does not promote conflicting incentives

The types of policies used to reduce carbon emissions will differ over time as some issues emerge as more powerful problems to be addressed, requiring new solutions.  Policies can be national or regional, or require international cooperation: bilateral, multinational or at the global scale.  Climate change mitigation is clearly a global problem, but one which includes national consideration such as energy, transport, land use and manufacturing policy, and as such, domestic and international policies will be needed to provide incentives for mitigation. 

There are many methods and procedures that form a part of policy but are not legally enforced.  Awareness campaigns, education and information dissemination, social movements, awards, and climate action naming and shaming might each enrol people or organisations to take action to reduce emissions.  Other potentially effective ways of reducing carbon emissions without recourse to legally binding policy include voluntary commitments, schemes or agreements, contracts, and, sanctions for failure to comply with agreed targets. 

While these strategies might play a role in the policy mix, I’ll consider just three types of high impact policy, those aimed in particular at reducing emissions from energy use: Imposed standards, market instruments and financial instruments.

Climate science models and the scientific method: experimentation verses deduction?

Is this science and is it valid: What would Thomas Hobbes think?

In Hobbes view, Boyle’s experimental solution to the problem of order was not possible; it was not effective; and it was dangerous. (Shapin and Schaffer 1985: 80-81).

In discussing the methods of climate science, the use of models and the process of simulation are often mentioned as either a key strength or key weakness of the science.  While climate models receive a great deal of attention (and funding), they are generally a very marginal part of the science – much more time is spent examining actual data, identifying relevant data sources, developing statistical methods and making sure that observations and calculations are contextualised in terms of other data sets.  The fact that some statistical methods assessing correlations in actual data is also called modelling is confusion.

By modelling, I will refer here only to simulation using models, a type of experimentation.  I will contrast modelling with the statistical analysis of actual data to determine specific correlations that does not depend on extrapolation or simulation.  While examples of either approach can be contested, the issue I am concerned with here is the validity of simulation and experimentation using models in climate science.  This issue is fundamental if we are to understand the criteria such modelling must meet if it is to follow the scientific method. 

The scientific method seems to be one of the more straightforward issues in climate science - we all know what the scientific method is, right? We agree with the Oxford English Dictionary that it is “a method of procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses” I assume.  But let's go back to the 17th Century for a moment to understand the emergence of the concept.  The status of experimentation was the source of an important dispute between Robert Boyle and Thomas Hobbes during the 1660s and 1670s.  The disagreement between Boyle and Hobbes is analysed in great detail by Steven Shapin and Simon Schaffer in their book Leviathan and the Air-Pump (Shapin and Schaffer 1985).  The book examines, among many its themes, the boundaries and methods of science in relation to questions of political philosophy.  This is a good place to start because there were two competing approaches to “the” scientific method, best expressed in terms of the relationship between scientist Robert Boyle and the political philosopher Thomas Hobbes, or rather the science and political thought of Boyle and the political thought and science of Hobbes.  Hobbes and Boyle are key figures in the Enlightenment tradition, their approach to method being that of the mechanistic philosophy while their epistemology developed along similar lines within the rationalist tradition, but where they differ is in the status of experimentation itself.

Holocaust Denial and Climate Change Denial - part 1

Climate Change? - Its all down to sunspots, right

One thing that should be made very clear: any attempt to try to link the views of those who oppose the conventional climate science to Nazism in any form is misguided and unfair. Goodwin's law of Nazi analogies (sometimes stated as follows: as an online discussion grows longer, the probability involving a comparison with the Nazis or Hitler approaches 1) implies that such comparisons are overused and by trying to create guilt by association with the word "denial" is in my view an example of Goodwin's law and its corollary that we should avoid glib association of a point of view with the Nazis. Holocaust denial is often part of a strategy to disassociate the extreme right with the systematic murder of millions of people in order to make an extreme right wing or anti-Semitic agenda more attractive. Holocaust denial historians ignore evidence or rely on fabricated evidence and they imply the existence of huge conspiracy theory on the part of eye witnesses and conventional historians. Those who voice opposition to the conventional views of climate science do so for many motives, as I discuss elsewhere, but however superficially similar the methods of some opponents of the conventional climate science could ever be to those of holocaust deniers, they could never have the same sneer at suffering that exemplifies the nasty agenda underlying their falsification of history.  In short calling the opponents of the conventional view of climate science “deniers” as a smear strategy is wrong.

The reality, though, is that names matter, which is why name calling matters: coining the right name for your opponents, or the object of your opposition is crucial - in the UK the expression "Franken food" still resonates with the general public when considering genetically modified foods, and in the abortion debate, both sides control their image by stating they are pro something - and controlling your own name is an important part of controlling your image, which is why enhanced interrogation techniques are sanctioned, not torture, why politicians only ever misspeak, fudge or are economical with the truth, why the Climate Research Unit email controversy is framed as "Climategate" and why holocaust deniers prefer to be called revisionists. Pejorative names have been coined and applied to those who believe that anthropogenic climate change is a reality, including the climate scientists whose research illustrates a clear link: alarmists, warmists, true believers or team hockystick. The implication is clear: add a context to the opponents' view (alarm, warming rather than climate change, dogmatic, imply the hockystick graph is based on bad science) and extra ( negative) information is coupled to the label. Instead those who hold this view prefer the expressions "the consensus view" or express their beliefs in terms of the scientific consensus in general to indicate that the basic science is settled. The implication of this is also clear - the argument is over, the science says anthropogenic climate change is happening, reduce emissions or face the consequences.