Critical Realim in Environmental and Social Sciences

Richards (1990) initiated debate on the possibility of the adoption of a realist perspective toward research in the environmental sciences (specifically geomorphology) by criticising the then emphasis on rationalist (hypothetico-deductive) methods.

The ontology of Critical Realism (CR) theorises that reality exits independently of our knowledge of it or scientific research or theories about it, and that it is structured into three levels:

  1. ‘Real’ natural generating mechanisms
  2. actual events caused by the real mechanisms
  3. empirical observations of the actual events

The separation these three levels impose between real processes and human observation means that whilst reality exists objectively and independently, we cannot observe it. Therefore perception and cognition are important components of our knowledge about the real world. In this way, critical realism sits as an alternative between positivism and relativisms, between the nomothetic and the idiographic, and between determinist and stochastic perspectives (Sayer 2000).

Whilst mechanisms are time and space invariant, actual events are not because they are realisations of the generating mechanisms acting in particular conditions and contingent circumstances. The history and geography of events matters. Identical generating mechanisms will not produce identical events at different locations in space and time.

CR does not claim absolute truth; rather it understands science is a method to progress towards understanding true reality. A critical realist approach does not require falsification or predictive success – theories are proven through consistency of theory and explanation at multiple time and space scales. Thus, it emphasises looking at systems within their context and undertaking multidisciplinary scientific activity.

CR has been suggested as a useful perspective for examining environmental (and social) systems for several reaons;

  1. It addresses systems and their elements in context. This is very important given the complex (multiple interacting elements), ‘open’ (energy and mass able to flow across system boundaries) nature of many environmental systems (von Bertalanffy 1950).
  2. It does not attempt prediction of time and space dependent environmental events and phenomena, the accuracy of which is logically impossible to verify (Oreskes et al. 1994, Oreskes 2000).
  3. It provides a more holistic and multi-disciplinary approach to studying environmental systems. Such a perspective is consistent with other other theoretical frameworks (e.g. General Systems Theory, Gestalt Systems, Hierarchy Theory) and as advocated elsewhere in the environmental sciences (e.g. Naveh 2000).

As Sayer (2000) notes; “Realists expect concrete open systems and discourses to be much more messy an ambiguous than our theories”. That is, realists don’t expect their model results to match empirical observations. Rather, the key is to develop an understanding of the relevant causal structures and mechanisms. Characteristically realist questions are:

  • What does the existence of this object presuppose?
  • Could object/process A exist without object/process B?
  • What is it about the structure of this object which enables it to do certain things?

Many landscapes are characteristic of the open, complex systems Richards and Sayer are referring to. Multiple interacting actors and elements are combined with flows of energy and mass and, when humans are in the landscape, meaning and value into and out of them. At the human scale, observed and located in the real world, landscapes exist in a unique time and place – the non-ergodic nature of the universe makes individual events within them virtually unreproducible (Kauffman 2000). In these systems history and geography are important. Adopting a realist perspective toward modelling of these systems, whilst not offering predictions of their future states, offers an approach to better understand them and inform debate about their future.

References
von Bertalanffy, L. (1950) The Theory of Open Systems in Physics and Biology Science 111 p.23 – 29

Kauffman, S. (2000) Investigations. Oxford: Oxford University Press

Naveh, Z. (2000) What is Holistic Landscape Ecology? A Conceptual Introduction. Landscape and Urban Planning 50 p.7 – 26.

Oreskes, N., Shrader-Frechette, K. and Belitz, K. (1994) Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences, Nature 263 p.641 – 646.

Oreskes, N. (2000) Why Predict? Historical Perspectives on Prediction in Earth Science In Sarewitz, D., Pielke Jr., R.A., and Byerly, Jr., R. (Eds) Prediction: Science, Decision Making and the Future of Nature. Washington D.C.: Island Press.

Richards, K. (1990) ‘Real Geomorphology’. Earth Surface Processes and Landforms 15 p.195 – 197.

Richards, K., Brooks, S., Clifford, N., Harris, T. and Lane, S. (1997) Theory, Measurement and Testing in ‘Real’ Geomorphology and Physical Geography In Stoddart, D. (Ed.) Process and Form in Geomorphology. London: Routledge.

Sayer, A. (2000) Realism and Social Science. London: Sage

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