“Saber Que No Estaba Sola; Knowing I Was Not Alone”: A Community’s Organizing Through Technology for Resilience

Maya Blitch et al.

Management Communication Quarterly2026https://doi.org/10.1177/08933189251415165article
AJG 2ABDC B
Weight
0.50

What the paper says

Socially and financially disadvantaged communities are disproportionately affected by increasingly frequent and cascading disasters, leaving them limited time to prepare, respond, and learn. Existing theory about resilience in disaster situations rarely integrates cultural considerations and the role of technology into resilience practices. To address these gaps, this study employed an anticipatory resilience framework to analyze 22 in-depth interviews, with community members involved in designing and implementing a community-owned disaster data portal. Following research methods respecting the participants’ language and culture, our grounded theory analysis revealed three core categories used to develop a new theory of resilience. Culturally anchored digital resilience theory claims that culture shapes the sensemaking, adoption, and knowledge production processes in resilient practices, challenging dominant narratives that exclude those most affected by disasters. The findings show how cultural context and communication can support technology-infused resilience initiatives and provide guidance for developing culturally sustained resilience tools.

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https://doi.org/https://doi.org/10.1177/08933189251415165

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@article{maya2026,
  title        = {{“Saber Que No Estaba Sola; Knowing I Was Not Alone”: A Community’s Organizing Through Technology for Resilience}},
  author       = {Maya Blitch et al.},
  journal      = {Management Communication Quarterly},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/08933189251415165},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.