Aldrich's (2011) study of six tsunami-affected fishing hamlets in Nagapattinam, Tamil Nadu, found that villages with strong caste- or parish-based councils recovered faster after the 2004 Indian Ocean tsunami — councils negotiated with NGOs and prepared beneficiary lists — but systematically excluded women, Dalits, migrants, and Muslims from recovery aid, while villages without councils recovered more slowly with almost no recorded exclusion. Because the study acknowledges that its six hamlets do not constitute a random or representative sample, its conclusion leaves open a single future-research question: to 'investigate the externalities of social capital in post-disaster situations in multiple contexts and time periods' — that is, whether this speed–exclusion trade-off holds beyond those hamlets, and under which conditions council-mediated recovery excludes marginalized subgroups (women, Dalits, migrants, Muslims) and when it does not, with measurement of bonding, bridging, and linking social capital sensitive to the local institutional forms.

Background

Social capital — the networks, norms, and trust that enable collective action — is conventionally divided into three forms: bonding capital (dense ties within a homogeneous group), bridging capital (ties across heterogeneous groups), and linking capital (vertical ties between a community and external institutions or resource holders). A large body of post-disaster research argues that communities with richer social capital recover faster from catastrophes. The 2004 Indian Ocean tsunami devastated the coast of Tamil Nadu, southeast India, destroying housing, boats, and fishing gear in coastal villages. In an ethnographic study of six fishing hamlets (populations 200–1200) in Nagapattinam district, Aldrich (2011) examined how local social organization shaped recovery. The key institutions were uur panchayats — informal, caste-based hamlet councils that organize the fishing-caste community — and, for Christian fishing communities, Roman Catholic parish councils. Hamlets with active councils recovered markedly faster: the councils acted as one-stop shops, negotiating with non-governmental organizations (NGOs), preparing beneficiary lists, and channeling reconstruction aid to their members. But this mobilizing capacity had exclusionary externalities: women, Dalits (communities historically placed at the bottom of the caste hierarchy, many of them landless laborers rather than caste fishers), migrants, and Muslims — groups poorly represented in or entirely outside the councils — were systematically omitted from beneficiary lists and aid flows. Villages without strong councils recovered more slowly but showed almost no recorded exclusion. A corroborating 63-village survey found roughly 16 percent of villages reporting that eligible Dalit or non-member households received no relief, and independent research on South Indian fishing communities after the tsunami reached consistent conclusions (Bavinck, 2008). Aldrich (2011) thus poses a speed–exclusion trade-off: the very closure and density of bonding and linking capital that accelerates collective recovery also reproduces caste- and gender-based exclusion in the distribution of recovery resources. The study is explicit that this finding rests on a small, non-random sample of six case villages plus secondary reports — in the paper's words, the hamlets 'do not constitute a random or representative sample' — and its conclusion accordingly poses a single open future-research question: 'Future research should seek to investigate the externalities of social capital in post-disaster situations in multiple contexts and time periods.' The paper grounds this call in a methodological caveat from its literature review: because social capital does not manifest itself in the same form across time and societies, its measurement must be sensitive to the historical period and cultural environment under investigation, and standard Western instruments did not map well onto the empirical realities of Indian states, where kinship, caste, and religion ties best reflect social resources. Its motivating normative concern, in the paper's words, is to better understand 'the factors which can expedite or block efficient and equitable recovery.'

Problem Statement

Aldrich (2011) leaves open, in the words of its conclusion, that 'Future research should seek to investigate the externalities of social capital in post-disaster situations in multiple contexts and time periods.' Because the study acknowledges that its six Nagapattinam hamlets do not constitute a random or representative sample, the open problem is whether the documented speed–exclusion trade-off generalizes beyond them: across other disaster-affected settlements and households — in multiple regions, disaster episodes, and time periods — does council-mediated recovery through caste-based uur panchayats and Roman Catholic parish councils again combine faster collective recovery with systematic exclusion of women, Dalits, migrants, and Muslims from the distribution of recovery aid, and under which institutional, demographic, and aid-supply conditions does it exclude marginalized subgroups, and when does it not? The open problem has three parts: (i) whether the speed–exclusion trade-off generalizes across additional contexts and time periods, together with the contexts, time periods, and data sources that would test it; (ii) the institutional, demographic, and aid-supply conditions under which council-mediated recovery excludes marginalized subgroups and when it does not; and (iii) measurement of bonding, bridging, and linking social capital sensitive to the historical period and cultural environment. Consistent with the source's methodological grounding, any such investigation must measure bonding, bridging, and linking social capital in ways sensitive to the historical period and cultural environment under investigation: standard Western instruments (literacy, voter turnout, membership in horizontal associations, density of formal organizations) do not map well onto Indian caste- and parish-based realities, where kinship, caste, and religion ties best reflect social resources. The source's motivating normative concern, in its own words, is to better understand 'the factors which can expedite or block efficient and equitable recovery'. The paper's own policy recommendations to planners are that recovery and rehabilitation plans should not destroy existing social capital through resettlement (evacuating in socially intact groups where possible), that bonding and linking social capital should be expanded so as to include excluded groups and develop outreach skills for peripheral residents, and that vulnerable communities' bonding and linking networks should be built up.

References

  1. Daniel P. Aldrich (2011), 'The Externalities of Strong Social Capital: Post-Tsunami Recovery in Southeast India', Journal of Civil Society 7(1):81–99. doi:10.1080/17448689.2011.553441, https://doi.org/10.1080/17448689.2011.553441
  2. Daniel P. Aldrich (2012), 'Building Resilience: Social Capital in Post-Disaster Recovery' (book), University of Chicago Press. doi:10.7208/chicago/9780226012896.001.0001, https://doi.org/10.7208/chicago/9780226012896.001.0001
  3. Daniel P. Aldrich and Michelle A. Meyer (2015), 'Social Capital and Community Resilience', American Behavioral Scientist 59(2):254–269. doi:10.1177/0002764214550299, https://doi.org/10.1177/0002764214550299
  4. Anuradha Mukherji (2014), 'Post-Disaster Housing Recovery: The Promise and Peril of Social Capital', Journal of Civil Society 10(2):119–143. doi:10.1080/17448689.2014.885787, https://doi.org/10.1080/17448689.2014.885787
  5. Olivier Rubin (2016), 'The political dimension of linking social capital: current analytical practices and the case for recalibration', Theory and Society 45(5):429–449. doi:10.1007/s11186-016-9277-8, https://doi.org/10.1007/s11186-016-9277-8
  6. Md. Masud-All-Kamal and S. M. Monirul Hassan (2018), 'The link between social capital and disaster recovery: evidence from coastal communities in Bangladesh', Natural Hazards 93(3):1547–1564. doi:10.1007/s11069-018-3367-z, https://doi.org/10.1007/s11069-018-3367-z
  7. Ming-Cheng Lo and Yun Fan (2020), 'Brightening the dark side of linking social capital? Negotiating conflicting visions of post-Morakot reconstruction in Taiwan', Theory and Society 49(1):23–48. doi:10.1007/s11186-020-09376-3, https://doi.org/10.1007/s11186-020-09376-3
  8. Kiyomi Kawamoto and Karl Kim (2019), 'Efficiencies of bonding, bridging and linking social capital: Cleaning up after disasters in Japan', International Journal of Disaster Risk Reduction 33:64–73. doi:10.1016/j.ijdrr.2018.09.010, https://doi.org/10.1016/j.ijdrr.2018.09.010
  9. Krishna Malakar and Trupti Mishra (2020), 'Revisiting cyclone Phailin: Drivers of recovery in marine fishing communities', International Journal of Disaster Risk Reduction 48:101609. doi:10.1016/j.ijdrr.2020.101609, https://doi.org/10.1016/j.ijdrr.2020.101609
  10. Andrés Marín, Örjan Bodin, Stefan Gelcich and Beatrice Crona (2015), 'Social capital in post-disaster recovery trajectories: Insights from a longitudinal study of tsunami-impacted small-scale fisher organizations in Chile', Global Environmental Change 35:450–462. doi:10.1016/j.gloenvcha.2015.09.020, https://doi.org/10.1016/j.gloenvcha.2015.09.020
  11. Abhay Joshi and Misa Aoki (2014), 'The role of social capital and public policy in disaster recovery: A case study of Tamil Nadu State, India', International Journal of Disaster Risk Reduction 7:100–108. doi:10.1016/j.ijdrr.2013.09.004, https://doi.org/10.1016/j.ijdrr.2013.09.004
  12. Roger Few, Nihal Ranjit, Vineetha Nalla, Garima Jain, Mark G. L. Tebboth, Chandni Singh, Vasudha Chhotray and Hazel Marsh (2023), '"We are not in the same boat": Representations of disaster and recovery in India', International Journal of Disaster Risk Reduction 92:103709. doi:10.1016/j.ijdrr.2023.103709, https://doi.org/10.1016/j.ijdrr.2023.103709
  13. Seonju Jang, Galen Newman, Michelle Meyer and Shannon Van Zandt (2024), 'Social Capital Theory and Quantitative Approaches in Measurements: Disaster Literature Focus', Natural Hazards Review 25(3). doi:10.1061/nhrefo.nheng-2009, https://doi.org/10.1061/nhrefo.nheng-2009
  14. Lucia Velotti and Maria Josephine D'Agostino (2026), 'Beyond the binary: a systematic review of the intersectionality of gender, social capital and disaster', International Journal of Emergency Services, pp. 1–16. doi:10.1108/ijes-11-2025-0073, https://doi.org/10.1108/ijes-11-2025-0073
  15. Momtaj Bintay Khalil, Brent C. Jacobs and Kylie McKenna (2021), 'Linking social capital and gender relationships in adaptation to a post-cyclone recovery context', International Journal of Disaster Risk Reduction 66:102601. doi:10.1016/j.ijdrr.2021.102601, https://doi.org/10.1016/j.ijdrr.2021.102601
  16. Vivi Alatas, Abhijit Banerjee, Rema Hanna, Benjamin A. Olken and Julia Tobias (2012), 'Targeting the Poor: Evidence from a Field Experiment in Indonesia', American Economic Review 102(4):1206–1240. doi:10.1257/aer.102.4.1206, https://doi.org/10.1257/aer.102.4.1206
  17. Huawei Han and Qin Gao (2019), 'Community-based welfare targeting and political elite capture: Evidence from rural China', World Development 115:145–159. doi:10.1016/j.worlddev.2018.11.010, https://doi.org/10.1016/j.worlddev.2018.11.010
  18. Maarten Bavinck (2008), 'Collective Strategies and Windfall Catches: Fisher Responses to Tsunami Relief Efforts in South India', Transforming Cultures eJournal 3(2). doi:10.5130/tfc.v3i2.923, https://doi.org/10.5130/tfc.v3i2.923