Archetype analysis in sustainability research: meanings, motivations, and evidence-based policy making

Abstract

2019.Archetype analysis in sustainability research: meanings, motivations, and evidence-based policy making. Ecology and Society 24(2):26.ABSTRACT. Archetypes are increasingly used as a methodological approach to understand recurrent patterns in variables and processes that shape the sustainability of social-ecological systems. The rapid growth and diversification of archetype analyses has generated variations, inconsistencies, and confusion about the meanings, potential, and limitations of archetypes. Based on a systematic review, a survey, and a workshop series, we provide a consolidated perspective on the core features and diverse meanings of archetype analysis in sustainability research, the motivations behind it, and its policy relevance. We identify three core features of archetype analysis: recurrent patterns, multiple models, and intermediate abstraction. Two gradients help to apprehend the variety of meanings of archetype analysis that sustainability researchers have developed: (1) understanding archetypes as building blocks or as case typologies and (2) using archetypes for pattern recognition, diagnosis, or scenario development. We demonstrate how archetype analysis has been used to synthesize results from case studies, bridge the gap between global narratives and local realities, foster methodological interplay, and transfer knowledge about sustainability strategies across cases. We also critically examine the potential and limitations of archetype analysis in supporting evidence-based policy making through context-sensitive generalizations with case-level empirical validity. Finally, we identify future priorities, with a view to leveraging the full potential of archetype analysis for supporting sustainable development.

Mapping social-ecological systems archetypes

“…Our study also contributes to a growing literature characterizing systems archetypes in SES [14,15,40]. The concept of archetype, first introduced by Forrester [47], refers to canonical structures or causal building blocks to many dynamical systems and their managerial problems.…”

“…Clustering SES Identifying SES archetypes from data is in essence a clustering problem, that is, a classification task of multiple elements by some measure of similarity. Identifying archetypes or systems' typologies is useful because it allows comparison between different cases with similar profiles, they reduce dimensionality, and facilitate extrapolation between cases with similar characteristics [14,15]. Numerous methods exist to perform clustering, but before explaining the details of our choices, first we present a brief overview of what others have done when classifying SES and how our work improves previous efforts.…”

A review of models of natural pest control: toward predictions across agricultural landscapes

“…We propose that filling this methodological gap requires an approach akin to middle-range theories, providing explanations that are valid in multiple cases, but within a narrower range of conditions than grand theories (P. Meyfroidt et al, 2018). Similar needs in sustainability research have led to an increase in the use of so-called archetypes, i.e., "context-sensitive, generalized models of sustainability problems, dynamics or strategies with case-level empirical validity" (Oberlack et al, 2019). Archetype approaches are particularly useful for capturing the critical details of a phenomenon with highly heterogeneous cases and for employing these details towards contextually explicit generalizations.…”

“…The derivation of archetypes of heterogeneous real-world systems requires that multiple cases be similar with respect to defining features of the studied phenomenon and that these cases share some key attributes (Oberlack et al, 2019). Natural pest control seems to respond idiosyncratically to land-use gradients across different systems, but cases show similar responses when grouped according to system characteristics and functional traits (Karp et al, 2018;Martin et al, 2019).…”

“…Most archetype models thus fall short of reproducing key characteristics of socioecological systems, such as hysteresis, thresholds and feedbacks. These limitations can be partly attributed to the disproportionate focus of sustainability research on causal effects rather than causal mechanisms (Patrick Meyfroidt, 2016), which has led to additional concerns with respect to model causality (Oberlack et al, 2019).…”