On Modelling in Memetics - Bruce Edmonds
Instead of working historically I wish to characterise the field in a functional way; namely:
the application of models with an evolutionary or genetic structure to the domain of (cultural) information transmission.
Similar to other developing fields there is a natural progression of questions. An initial question might be whether such an application is at all useful. Following on from that is the question of in what ways is such application useful. Finally a mature field should be concerned with the question of determining under exactly what circumstances is such an application useful. At the moment, although a positive answer to the first question is frequently assumed by academics in the field, the battle for its general acceptance is far from won. Work has only just began to touch on the second question.
At the moment there are many memetics models of different kinds. A glance through this journal alone shows many different models of what a meme is or could be. This is healthy, it means that the mechanisms of variation are truly operative, but for the field to evolve what we also need good selection criteria for such models. While older fields have had time for appropriate selection mechanisms to be themselves evolved, a new field such as memetics is in the position that there is a great deal of uncertainty about what might constitute a good memetic model.
In fields without selection criteria that are grounded outside the field (e.g. evidence, the theories of other sciences etc.), there is a strong tendency to adopt a sort of default set of selection criteria, namely: the extent to which the model uses established language and techniques from the field and the extent to which the model is embedded in the field itself, i.e. it builds on other models, criticises other models, examines the thought of other models etc.*1.
Now, while such criteria are fine for maintaining the coherence of a field and for entrenching the position of those people already in the field, it is not a good set of criteria for ensuring the long term growth and success of the body of knowledge that makes up the field itself. Such criteria are widespread in a field like economics. Such long-term success will only come about when people outside the field see the memetic models as useful to them and this will only happen quickly if they feel they can rely on them. The reliability of the models will depend on the extent that the field is grounded in something established (real-world studies and/or accepted models from outside the field). In other words the success of the field (as opposed to the success of academics within the field), will depend largely on the embedding of the field within the wider academic landscape. It is notable that there appears to be a strong correlation between the success of a field and its openness to ideas from outside. A susceptibility to Kuhnian paradigm shifts  seems to allow fields to adapt better to possible niches in the wider society*2.
Of course any model selection criteria must take into account the type of model. There are almost as many types of model as there are reasons for modelling. Two dimensions along which they differ are in their abstractness and their temporal direction. One model may be for the prediction of events (forwards), and another for explanation of events that have already occurred (backwards), some will be metaphors for use in thinking about situations (abstract) and others will be bald data models of some aspect of the real world (concrete). In figure 1, I illustrate this categorization with a couple of models on these two axes.
Figure 1. Some different types of memetic models, with their direction of explanation
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