Permanent record
RIR-105 · Logged 13 July 2026
After the flood: how do informal care networks shape recovery?
Formal recovery metrics can miss the unpaid, relational work that gets households back on their feet. This project maps those care networks and the burdens they carry after major floods.
In plain words
After a flood in a coastal city, much of the work that gets households back on their feet is unpaid help people give one another. How does that care affect how quickly and fairly families recover?
Primary research question
How do informal care networks affect the speed and fairness of household recovery after urban flooding?
Knowledge gap
What remains worth asking
Household recovery measures undercount relational and unpaid care work.
Potential contribution
Why it may matter
The evidence could make recovery policy more responsive to unequal care burdens.
Academic placement
Academic fields and topic tags
Study frame: Coastal cities · Method signals: Social network analysis, Oral histories
Possible study pathways
One question, different levels
Research master’s
Map care networks in one flood-affected community.
Doctoral
Compare network change and household recovery longitudinally across multiple disasters.
- originality
- Advanced
- methodology
- Advanced
- Data access
- Moderate
- ethics
- Advanced
Quality and audit
90/100 quality
Safeguard-based audit was not recorded under the prior standard.
- High ethical sensitivity
- Strong theoretical and practical value
- Verified paper provenance
This older record can be checked against the current standard on request. It changes only if every academic gate and independent safeguard passes.
Sign-in required · uses one AI creditProvenance
Research Idea curation
- DOI and bibliographic metadata independently resolved
- Exact source location supplied
- Research direction is transparently marked as AI-inferred
The public contributor code contains no name or account email.
APA 7 source
Gray, S. (2023). Rethinking disaster utopia: The limits of conspicuous resilience for community-based recovery and adaptation. Disasters, 47(3), 608–629. https://doi.org/10.1111/disa.12567
Discussion and conclusion
This is an AI-inferred direction. The source authors did not state it as a recommendation.
Open source ↗