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Doctoral thesis . 2016
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Decision making, agenda setting, and preference shaping in Ghana’s agricultural climate change adaptation policy regime: a political ecological perspective

Authors: Sova, C;

Decision making, agenda setting, and preference shaping in Ghana’s agricultural climate change adaptation policy regime: a political ecological perspective

Abstract

Where power lies and how it is conceived in studies of environmental governance is not often discussed. The development and implementation of agricultural climate change adaptation policies calls on diverse stakeholder groups, each with their own interests and objectives. How debates around policy design and content are resolved is shaped by the power and influence of actors within the adaptation regime. Smallholder farmers are often considered marginalized within the adaption policy development and implementation process in Ghana, and in the developing world more broadly. This study seeks to demonstrate the ways in which smallholder farmers are susceptible to domination by other actors within adaptation policy regimes, and to identify the features of those regimes (institutional and otherwise) that enable one group to wield influence over another. This dissertation seeks to make power the subject of analysis instead of, in the words of Mitchell, "an answer known in advance", providing a more thoroughgoing synthesis of power than previous treatments in environmental governance literature. Drawing on the field of political ecology, I aim to provide an alternative to the predominant view of powerlessness among smallholders as a product of limited capability or adaptive capacity (i.e. power-to) and towards powerlessness as a relational construct (i.e. power-over). To that end, I adopt Steven Lukes’ dimensional framework of power-as-domination to illustrate that associating power with 'behaviorist' (i.e. visible decision making and agenda setting) theories alone is to adopt too narrow a view. Instead, a third dimension of power, preference shaping, which examines the way in which certain actors are "denied privileged access to their own reasons for actions" is necessary. I extend Lukes' analytical framework to include three replicable sources of preference shaping: dominant narratives and discourses, prevailing rationalities of governance, and systemic institutional bias. The results suggest that, true to political ecology, the study of adaptation policy in Ghana begins in contradiction: while climate adaptation policy is politically charged and contested at international levels, and it remains surprisingly devoid of politics at the sub-national levels. Adaptation policy development has been effectively 'rendered technical' in Ghana, eroding the need for active participation from non-experts in policy decision making, and leading to the neglect of important underlying political forces (a-politicization) that shape adaptation outcomes through policy implementation. This thesis extends important findings from development theory, particularly the work of Ferguson and Murray Li, in to the adaptation context, builds on an expansive body of power in social science literature, and develops a novel methodology for empirically mapping influence in complex system regimes.

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United Kingdom
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green