Direction not Destination

Thursday, 31 May 2007

Critical Realism for Environmental Modelling?

As I've discussed before, Critical Realism has been suggested as a useful framework for understanding the nature of reality (ontology) for scientists studying both the environmental and social sciences. The recognition of the ‘open’ and middle-numbered nature of real world systems has led to a growing acceptance of both realist (and relativist - more on that in a few posts time) perspectives toward the modelling of these systems in the environmental and geographical sciences.

To re-cap, the critical realist ontology states that reality exits independently of our knowledge, and that it is structured into three levels: real natural generating mechanisms; actual events generated by those mechanisms; and empirical observations of actual events. Whilst mechanisms are time and space invariant (i.e are universal), actual events are not because they are realisations of the real generating mechanisms acting in particular conditions and contingent circumstances. This view seems to fit well with the previous discussion on the nature of 'open' systems - identical mechanisms will not necessarily produce identical events at different locations in space and time in the real world.

Richards initiated debate on the possibility of adopting a critical realist perspective toward research in the environmental sciences by criticising emphasis on rationalist (hypothetico-deductive) methods. The hypothetico-deductive method states that claims to knowledge (i.e. theories or hypotheses) should be subjected to tests that are able to falsify those claims. Once a theory has been produced (based on empirical observations) a consequence of that theory is deduced (i.e. a prediction is made) and an experiment constructed to examine whether the predicted consequences are observed. By replicating experiments credence is given to the theory and knowledge based upon it (i.e. laws and facts) is held as provisional until evidence is found to disprove the theory.

However, critical realism does not value regularity and replication as highly as rationalism. The separation of real mechanisms from empirical observations, via actual events, means that "What causes something to happen has nothing to do with the number of times we have observed it happening". Thus, in the search for the laws of nature, a rationalist approach leaves open the possibility of the creation of laws as artefacts of the experimental (or model) ‘closure’ of the inherently open system it seeks to represent (more on model ‘closure’ next time).

The separation of the three levels of reality means that whilst reality exists objectively and independently, we cannot observe it. This separation causes a problem - how can science progress toward understanding the true nature of reality if the real world is unobservable? How do critical realists assess whether they have reached the real underlying mechanisms of a system and can stop studying it?

Whilst critical realism offers reasons for why the nature of reality makes the modelling of 'open' systems tricky for scientists, it doesn't seem to provide a useful method by which to overcome the remaining epistemological problem of knowing whether a given (simulation) model structure is appropriate. In the next few posts I'll examine some of these epistemological issues (equifinality, looping effects, and affirming the consequent) before switching to examine some potential responses.

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