“Localization” in Fragile Spaces: A Comparative Networks Evaluation of Community-Based Programmes in Pakistan and Afghanistan

ABSTRACT

Conventional externally-driven development interventions have shifted towards ‘localized,’ ‘bottom-up,’ participatory approaches, such as Community-Driven Development (CDD). However, structural dynamics of conflict-prone spaces continue to challenge their sustainability. Integrating content analysis, social network analysis (SNA), and qualitative comparisons (archival research and over 100 field interviews), this article examines the efficacy of CDD in Pakistan and Afghanistan. SNA of two World Bank programmes illuminates network properties of power and centralization, corresponding with key insights from fieldwork, including comparisons with Pakistan’s Rural Support Programmes. This mixed-method study reveals critical structural conditions that permit and/or constrain sustainable, locally-owned processes in fragile spaces.

KEYWORDS:

• International development policy
• Pakistan
• Afghanistan
• community-driven development
• social network analysis
• sustainable development
• fragility

Acknowledgments

Many thanks to the Smith Richardson Foundation World Politics and Statecraft Fellowship for supporting the fieldwork in Pakistan. I express much gratitude for support from many institutions and individuals that helped facilitate the fieldwork. Sincere thanks to George Mason University, the Schar School of Policy and Government, and my Dissertation Committee: Dr. Kenneth A. Reinert (Chair), Dr. Jennifer N. Victor, Dr. Peter Mandaville, and Dr. Enrique D. Arias.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Social capital ‘measures the strength of personal relationships, social network support, social norms, and civic participation in a country’ (2019). Table 1 Poverty Indicators: population in multidimensional poverty; under 5 mortality rate, infant mortality rate, and maternal mortality ratio.

2. Documentation reviewed: World Bank websites; operation manuals (ARTF, MDTF, World Bank manuals); impact evaluations; websites of Ministries; local project websites (no longer active); archival documents (i.e. brochures, newsletters, weekly, monthly, quarterly, annual development reports, proposals and agreements). Stakeholders of the NSP and RLCIP projects were interviewed during fieldwork in Pakistan.

3. Data coding was completed in an excel ‘edgelist’ (list of ties between nodes) indicating the source node, target node, label for the edge attribute/type of relations (numeric) and weights (all coded as 1). The network visualizations and metrics were obtained in both Gephi and UCINET.

4. Local project websites provided most material for the NSP and the RLCIP between 2014 to 2017. They were first accessed on October 2014, and reviewed until 2018. Websites became inactive before 2018. The content and networks analyses were completed as of 2017.

5. Fieldwork was completed between 2017–2019 and helped verify the network analysis. All field interview observations reflect this time period.

6. Written and verbal consent were retrieved from all research participants in this study. Research participants willing to go ‘on the record,’ are identified as per the author’s approved protocol for informed consent, from the George Mason University Institutional Review Board.

7. The NOC requirement was eased during the Covid-19 Pandemic, in early 2020, for relevant NGOs and INGOs to be able to provide Covid-19 related assistance.

8. *Indicators are taken from the most recent World Bank Statistics for Afghanistan and Pakistan found on Data.worldbank.org (2019).

9. Human Development Index (HDI) Score: Literacy, Life longevity, and GDP.

10. Average years a newborn expected to live under current mortality levels (Population Reference Bureau (PRB), World Population Data Sheet, 2015; International Data and Economic Analysis, USAID, 2017).

11. Percentage of people using improved sanitation facilities (WHO/UNICEF, Joint Monitoring Program (JMP) for Water Supply and Sanitation, 2015; International Data and Economic Analysis, USAID, 2017).

12. The percentage of population (both sexes 15+ years that are literate (From UNESCO, Institute of Statistics, UIS, Database, 2015) (International Data and Economic Analysis, USAID, 2017).

13. RLCIP directed graph with 77 nodes and 208 edges, computed in Gephi. Node Size, Colour: Eigenvector Centrality.

14. RLCIP directed graph with 77 nodes and 208 edges, computed in Gephi. Node Colour: Communities; Node Size: Betweenness Centrality; Edge Colour: Edge attributes, Modularity (at Resolution 1.0): 0.538; Number of Communities: 8; Gephi Algorithm: The Louvain Method. (Blondel et al., 2008). Gephi Resolution: (Lambiotte et al., 2009).

15. NSP directed graph, 136 Nodes and 645 Edges, computed in Gephi. Node Size and Colour: Eigenvector Centrality.

16. NSP directed graph, computed in Gephi. Node Colour: Communities; Node Size: Betweenness Centrality; Edge Colour: Edge attributes; Modularity (at Resolution 1.0): 0.454; Number of Communities: 8. Gephi Algorithm: The Louvain Method (Blondel et al., 2008). Gephi Resolution: (Lambiotte et al., 2009).

Additional information

Funding

This work was supported by the Smith Richardson Foundation [118418].

Notes on contributors

Elsa Talat Khwaja

Elsa Talat Khwaja received her Ph.D. in Public Policy from the George Mason University, Schar School of Policy and Government. Her specializations include qualitative research methods, international development policy, social capital and social networks. Her research centres on aid-effectiveness in fragile and conflict-affected spaces, with current focus in South Asia and the Middle East. She has a Master’s degree in Public and International Affairs, with a concentration on human security, from the University of Pittsburgh, and a Bachelor’s degree in Global Studies and Political Science from the University of Minnesota, Twin Cities.