Scaling up Social Accountability in Complex Governance Systems: A Relational Approach for Evidencing Sustainability

Resource type
Authors/contributors
Title
Scaling up Social Accountability in Complex Governance Systems: A Relational Approach for Evidencing Sustainability
Abstract
When social accountability interventions scale up and their sustainability depends on the interactions of many agents and system components, related results are rarely observable at the end of an intervention. The 2019 OECD Development Assistance Committee’s (OECD DAC) revamped evaluations criteria for assessing sustainability acknowledges that such results are often emergent, and should be monitored and evaluated with this in mind. It therefore emphasizes a turn towards assessing complex processes prospectively. It also asks evaluations to consider how likely it is that these results are evident at the time they are monitored or evaluated. However,the social accountability field continues to have gaps regarding doing this effectively in practice. This paper presents and provides evidence from testing an innovative operational approach that has promising potential to support this aim - a sequential, relational rubric. This approach can support practitioners to monitor, evaluate and learn about the causal processes of scale up of social accountability interventions with an eye towards sustainability i.e., considering prospective sustainability. It is grounded in systems thinking, co-production and social learning theory, as well as links with collective governance and social contract theory for development. Evidence yielded from the authors’ testing of this approach on a sample of diverse projects from the Global Partnership for Social Accountability (GPSA) program revealed that the alleged ‘absence of evidence’ dilemma of social accountability scale up is due to ill-fitting concepts and methods for assessment. It challenges existing assumptions and findings that claim that social accountabilityprocesses do not scale and are unsustainable. The authors propose that by using fit-for-purpose concepts and methods with a focus on social learning and compromise – also called a ‘resonance pathway to scale’ which this paper discusses in detail – it is possible to observe loosely coordinated scale up processes at work in many (but not all) social accountability interventions and identify tangible evidence of prospective sustainability. An important caveat is that these processes, the outcomes they generate, and the corresponding evidence often look qualitatively different than the original intervention design and predictions for scale-up at that point in time. This is because the process of deliberation and compromise inherent to social accountability work in dynamic local systems introduces changes and new conditions for uptake by diverse actors in the public sector, civil society, and donor institutions. The paper concludes that even relatively small-scale localized projects of three to five years with budgets of less than one million USD, across different contexts and sectors can produce processes and outcomes which contribute to many forms of sustainability, including via scaleup.Furthermore, the cross-fertilization of learning and aggregation of results for scale-up across projects within and beyond the GPSA (and other programs) can help monitoring evaluation and learning (MEL) and social accountability practitioners alike to deliver on a program’s mandate. Doing so can also create new knowledge for the wider social accountability field that siloed interventions, lacking suitable concepts and methods for assessing scale-up and prospective sustainability, often fail to produce. The paper ends with recommendations for taking forward this approach and the associated benefits, implications and required investments.
Place
Washington DC
Institution
World Bank
Date
2024.01
Accessed
13/02/2024, 13:08
Citation
Guerzovich, F., & Wadeson, A. (2024). Scaling up Social Accountability in Complex Governance Systems: A Relational Approach for Evidencing Sustainability. World Bank. http://documents.worldbank.org/curated/en/099248202082451403/IDU143be23531a0f714f561b91515c596de86102