I have been working on a research proposal to study whether and how constructs from Evolutionary Biology and Ecology might be useful in Evaluation. This is the first of two posts that come from some of the  introductory material in the proposal. The second is: Evolutionary and Ecological Constructs that may be Useful in Evaluation.

Can constructs drawn from the fields of Evolutionary Biology and Ecology be expanded beyond their traditional boundaries and find use in the field of Evaluation? Insights from a diverse population of disciplines suggests that the answer is “yes”.

Applicability Outside Disciplinary Boundaries

Genetic algorithms have been applied to product design (Balakrishnan & Jacob, 1996), software engineering (Boehm & Egyed, 1999), and planning (Davies, 2020). The evolutionary adaptability of “failure” has been used to understand effective programming and planning (Davies, 2010). Selection and retention dynamics figure prominently in analyses of scientific knowledge development (Bradie & Harms, 2020) and (Campbell, 1960); and technology (Basalla, 1988). Evolutionary constructs have been applied to analyses of the birth and extinction of organizational forms (Hannan & Freeman, 1989), and to organizational learning (Davies, 1998). Evolutionary and adaptive theory has been applied to a wide range of scaling effects – life sciences, cities, prediction capability, corporations (West, 2017).

Applicability to Evaluation

Set within this range of application are specific references to Evaluation. Picciotto (2019) has probed the implications of Campbell’s evolutionary epistemology for evaluation theory. Urban, Hargraves, and Trochim (2014) propose “evolutionary evaluation” as a framework for aligning program phases with types of validity.

(Morell, 2020a);(Morell, 2020b) has identified evaluation questions that would be unlikely to reveal themselves absent evolutionary biological and ecological lenses. Examples include queries about population size for different types of programs, rates of change for program content and structure over time, time between intervention and observed effect, and diversity of programs and program effects that flow from interventions. He makes two general arguments.

Discrete constructs:
There are specific constructs drawn from Ecology and Evolutionary Biology that can be applied to evaluation. A few examples are evolution, the biotic hierarchy, selection pressure, mutation, and fitness landscapes.

Characteristics of inquiry:
Scientific fields have their own ways of approaching inquiry. For instance, with respect to the use of models, favored methodologies, the human capital makeup of research teams, and the characteristics of acceptable answers. While each of these elements has value in its own right, each affects some of the others, thus resulting in emergent network effects. Because of these emergent consequences, the unique perspectives of a field cannot be understood only in terms of the aggregate consequences of each element.

References

Balakrishnan, P. V., & Jacob, V. S. (1996). Genetic Algorithms for Product Design. Management Science, 42(8), 1105-1117.
Basalla, G. (1988). The Evolution of Technology. Cambridge and New York: Cambridge University Press.
Boehm, B., & Egyed, A. (1999). Optimizing software product integrity through life-cycle process integration. Computer Standards & Interfaces, 21, 63 – 75.
Bradie, M., & Harms, W. (2020). Evolutionary Epistemology. In E. N. Zalta (Ed.), Stanford Encyclopedia of Philosophy. Retrieved from https://plato.stanford.edu/archives/spr2020/entries/epistemology-evolutionary/.
Campbell, D. T. (1960). Blind variation and selective retentions in creative thought as in other knowledge processes. Psychological Review, 67(6), 380 – 400.
Davies, R. (1998). Order and Diversity: Representing and Assisting Organisational Learningin Non-Government Aid Organisations. (PhD), University of Wales Swansea, Retrieved from http://www.mande.co.uk/wp-content/uploads/1998/Davies-R-1998-PhD-Thesis.pdf
Davies, R. (2010). Do we need a Required Level of Failure (RLF)? Retrieved from https://mandenews.blogspot.com/2010/10/do-we-need-minimal-level-of-failure-mlf.html
Davies, R. (2020). ParEvo — A Planning Tool. Retrieved from https://mscinnovations.wordpress.com/
Hannan, M. T., & Freeman, J. (1989). Organizational Ecology. Cambridge MA: Harvard University Press.
Morell, J. A. (2020a). Can Knowledge of Evolutionary Biology and Ecology Inform Evaluation? Blog: Evaluation Uncertainty: Surprises in Programs and Their Evaluations. Retrieved from http://jamorell.com/documents/Can_Knowledge_of_Evolutionary_Biology_and_Ecology_Inform_Evaluation.pdf
Morell, J. A. (2020b). Evolutionary Biology and Ecolology as a Valuable Framework for Some Evaluation. Retrieved from https://www.youtube.com/watch?v=urrHP8EV6Hs&t=3s
Picciotto, R. (2019). Donald T. Campbell’s Evolutionary Perspective and its Implications for Evaluation. Journal of Multidisciplinary Evaluation, 15(33), 1 – 15.
Urban, J. B., Hargraves, M., & Trochim, W. M. (2014). Evolutionary Evaluation: Implications for evaluators, researchers, practitioners, funders and the evidence-based program mandate. Evaluation and Program Planning 45 (2014) 127–139, 45, 127 – 139.
West, G. (2017). Scale: The Universal Laws  of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. New York: Penguin.

 

 

 

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