William C Wimsatt - Aggregativity: Reductive Heuristics for Finding Emergence (1997)
Rather than focusing on seeking the essential characteristics of emergence, Wimsatt's paper takes the opposite approach and attempts to pin down the set of properties for a property to be definitively non-emergent. We saw earlier that it's not a straightforward process to distinguish between the two in any case, with certain "obviously" linear-additive properties being a little more complex on inspection, and vice versa. Wimsatt throws in another nice example of nonlinear composition, that of volume under dissolution: the volume of a salt-water solute is actually less than the volume of either of its constituents. Sometimes, more is less.
The key thesis is that emergence is a consequence of certain organisational properties, combined with context-sensitivity of the parts that constitute this organisation. Non-emergent systems properties are termed "aggregates" by Wimsatt. To be truly aggregative, a property must be functionally invariant when its parts are subjected to any of the following transformations:
- intersubstitution (that is, rearranging or substituting parts for others)
- size scaling (adding or subtracting parts)
- decomposition and reaggregation (of parts)
- linearity
For the macro-scale systems property to not vary under any of these transformations, it is pretty clear that it must be radically functionally homogeneous. Wimsatt observes that the only paradigmatic aggregative properties are those governed by major laws of conservation: mass, energy, momentum and charge.
Perhaps the most rewarding movement of this argument is where Wimsatt takes it in the final couple of pages. With a background in the philosophy of biology, he writes on the structures that underlie natural selection and the models that we, as scientists, impose to understand them. Here, he criticises the "nothing but X" language of radical reductionism, such as in the oft-touted "genes are the only units of selection". However, if we take the complex dynamical systems that comprise the natural world and attempt to reduce them to a model based on one underlying constituent unit (the gene, the agent, the neuron), we cannot then make claims to universality of our model: this is what Wimsatt terms the functional localisation fallacy. Such a decomposition is useful to study some aspects of a system, but it should be understood that it must be complemented by other such decompositions from different levels and angles.

Research from Cornell University, and published in this month's