Determinism and Total Explanation in the Biological and Behavioral Sciences


Should we think of our universe as law‐governed and ‘clockwork’‐like or as disorderly and ‘soup’‐like? Alternatively, should we consciously and intentionally synthesise these two extreme pictures? More concretely, how deterministic are the postulated causes and how rigid are the modelled properties of the best statistical methodologies used in the biological and behavioural sciences? The charge of this entry is to explore thinking about causation in the temporal evolution of biological and behavioural systems. Regression analysis and path analysis are simply explicated with reference to a thought experiment of painting three universes (clockwork, soup and conscious) useful for imagining our actual universe. Attention to historical, structural and mechanistic explanatory perspectives broadens the palette of methodologies available for analysing determinism in, and explanation of, biological and behavioural systems. Each justified methodology provides a partial perspective on complex reality. Is a total explanation of any system ever possible and what would it require?

Key Concepts:

  • A thought experiment delineating three universes – clockwork, soup, and conscious – assists in understanding statistical methodologies.

  • Neither extreme rigid determinism nor radical chancy indeterminism permit accurate depictions of a ‘Laplacian chance’, conscious universe.

  • Standard statistical methodologies related to the General Linear Model (GLM), such as regression analysis and path analysis, synthesise determinism and indeterminism in important ways (e.g. via error terms).

  • History of science illustrates the plurality of scientific methods.

  • Inferring causes using statistical analysis is not impossible.

  • Indeed, randomised experiments and rigorous statistical methodologies can licence causal claims.

  • An analogy from the physical sciences, displacement of springs, provides a running example for the variety of questions asked of system behaviour from statistical, historical, structural, and mechanistic perspectives.

  • Historical explanation and mechanistic explanation remain autonomous explanatory perspectives interested, respectively, in the origin and part‐whole structure of a biological or behavioural system.

  • The general methodological analyses here presented should be complemented with more concrete case studies of, for example, sexuality, intelligence, autism, and ‘criminality’.

  • Are explanations from distinct explanatory perspectives ‘miscible’ or do we reach an ‘impasse when we attempt to integrate and mix them?

Keywords: models; causes; explanation; statistics; regression analysis; path analysis; history; mechanism; scientific methods; genetics

Figure 1.

Diagram illustrating the interrelations among the factors which determine the weight of guinea pigs at birth and at weaning (33 days).



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Winther, Rasmus Grønfeldt(Jul 2014) Determinism and Total Explanation in the Biological and Behavioral Sciences. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1002/9780470015902.a0024143]