Sahide, Muhammad A.K. and Fisher, Micah R. and Verheijen, Bart and Maryudi, Ahmad and Kim, Yeon-Su. and Wong, Grace Y. (2020) Sequential power analysis framework in assessing social forestry outcomes. MethodsX, 7. pp. 1-4. ISSN 22150161
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Abstract
We extend the Actor-Centred Power framework to consider dimensions beyond the life of community natural resource management partnership initiatives by examining social forestry partnership projects in Indonesia. We do this by examining how power constellations realign across the temporal phases that operationalize project partnerships. We propose a sequential power analysis framework that examines power in three parts. The framework first proposes a method for historicizing actors into their power background. Second, we present mode for examining the arrival of a partnership scheme, which we call the power delivery phase. Third, we highlight approaches for examining the way power relations are adjusted, whether reinforced or reconfigured, by introducing an approach for examining programmatic outcomes of social forestry partnership schemes. This article thus provides broadly applicable but targeted guide for the researchers collecting data and seeking to make sense of power relations on community forest partnership schemes in various contexts. This framework is particularly useful for analysing equity and justice dimensions by highlighting who benefits and who loses. • Sequential Power Analysis (SPA) methodology is rooted in interest based and historical power framework. • SPA is consisted of three parts: power background, power delivery, and power adjustment • SPA framing provides a protocol for researchers to collect data © 2020
Item Type: | Article |
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Additional Information: | cited By 4 |
Uncontrolled Keywords: | Power adjustment; Power background; Power delivery; Sequential power analysis; Sequential power analysis (SPA) |
Subjects: | S Agriculture > SD Forestry |
Divisions: | Faculty of Forestry |
Depositing User: | Wiwit Kusuma Wijaya Wijaya |
Date Deposited: | 17 Oct 2024 06:38 |
Last Modified: | 17 Oct 2024 06:38 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/7263 |