2019
Design and quality criteria for archetype analysis
EISENACK, Klaus; Sergio VILLAMAYOR-TOMAS; Graham EPSTEIN; Christian KIMMICH; Nicholas MAGLIOCCA et al.Základní údaje
Originální název
Design and quality criteria for archetype analysis
Autoři
EISENACK, Klaus; Sergio VILLAMAYOR-TOMAS; Graham EPSTEIN; Christian KIMMICH; Nicholas MAGLIOCCA; David MANUEL-NAVARRETE; Christoph OBERLACK; Matteo ROGGERO a Diana SIETZ
Vydání
Ecology and Society, Wolfville, Resilience Alliance, 2019, 1708-3087
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
50704 Environmental sciences
Stát vydavatele
Kanada
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 3.890
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14230/19:00111515
Organizační jednotka
Fakulta sociálních studií
UT WoS
EID Scopus
Klíčová slova anglicky
abstraction; archetype analysis; generalization; ideographic trap; interdisciplinary collaboration; panacea; pattern; research design; social-ecological systems; qualitative; quantitative; validity
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 26. 3. 2020 15:22, Mgr. Blanka Farkašová
Anotace
V originále
A key challenge in addressing the global degradation of natural resources and the environment is to effectively transfer successful strategies across heterogeneous contexts. Archetype analysis is a particularly salient approach in this regard that helps researchers to understand and compare patterns of (un)sustainability in heterogeneous cases. Archetype analysis avoids traps of overgeneralization and ideography by identifying reappearing but nonuniversal patterns that hold for well-defined subsets of cases. It can be applied by researchers working in inter- or transdisciplinary settings to study sustainability issues from a broad range of theoretical and methodological standpoints. However, there is still an urgent need for quality standards to guide the design of theoretically rigorous and practically useful archetype analyses. To this end, we propose four quality criteria and corresponding research strategies to address them: (1) specify the domain of validity for each archetype, (2) ensure that archetypes can be combined to characterize single cases, (3) explicitly navigate levels of abstraction, and (4) obtain a fit between attribute configurations, theories, and empirical domains of validity. These criteria are based on a stocktaking of current methodological challenges in archetypes research, including: to demonstrate the validity of the analysis, delineate boundaries of archetypes, and select appropriate attributes to define them. We thus contribute to a better common understanding of the approach and to the improvement of the research design of future archetype analyses.