J 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

Impakt faktor

Impact factor: 3.890

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14230/19:00111515

Organizační jednotka

Fakulta sociálních studií

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.

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