A meta‐analysis of SES framework case studies: Identifying dyad and triad archetypes

Partelow, Stefan; Villamayor‐Tomas, Sergio; Eisenack, Klaus; Epstein, Graham; Kellner, Elke; Roggero, Matteo; Tschopp, Maurice (2024). A meta‐analysis of SES framework case studies: Identifying dyad and triad archetypes. People and nature British Ecological Society 10.1002/pan3.10630

Preview

Text Partelow__Villamayor-Tomas_et_al._2024_-_A_meta-analysis_of_SES_framework.pdf - Published Version Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND). Download (17MB) | Preview

1. There is a need to synthesize the vast amount of empirical case study research
on social-­ecological systems (SES) to advance theory. Innovative methods are
needed to identify patterns of system interactions and outcomes at different lev-
els of abstraction. Many identifiable patterns may only be relevant to small sets
of cases, a sector or regional context, and some more broadly. Theory needs to
match these levels while still retaining enough details to inform context-­specific
governance. Archetype analysis offers concepts and methods for synthesizing
and explaining patterns of interactions across cases. At the most basic level, there
is a need to identify two and three independent variable groupings (i.e. dyads and
triads) as a starting point for archetype identification (i.e. as theoretical building
blocks). The causal explanations of dyads and triads are easier to understand than
larger models, and once identified, can be used as building blocks to construct or
explain larger theoretical models.

2. We analyse the recurrence of independent variable interactions across 71 quan-
titative SES models generated from qualitative case study research applying
Ostrom's SES framework and examine their relationships to specific outcomes
(positive or negative, social or ecological). We use hierarchical clustering, prin-
cipal component analysis and network analysis tools to identify the frequency
and recurrence of dyads and triads across models of different sizes and outcome
groups. We also measure the novelty of model composition as models get larger.
We support our quantitative model findings with illustrative visual and narrative
examples in four case study boxes covering deforestation in Indonesia, pollution
in the Rhine River, fisheries management in Chile and renewable wind energy
management in Belgium.

Interest & Impact

Downloads

0 since deposited on 24 Apr 2024
0 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item