Aftermath: Infrastructure, Resources, and Organizational Adaptation in the Wake of Disaster
Bibliographic record
Abstract
Informal and emergent organizations play a vital role in disaster response, and are a central concern to crisis informatics. Prior research in the field has tended to focus on the activities of individual organizations during periods of disaster. Though unsurprising, this focus has led to limited understanding of the origins and long-term trajectories of these organizations or their participation in broader networks of informal response, whose individual membership, ideologies, and practices are often fluid and overlapping. In this paper, we examine the activities of informal organizations that mobilized in response to the 2015 earthquake in Nepal. Drawing on semi-structured interviews with 17 participants, we identify five categories of resources - funding, people, information, skills, and shared values - that these organizations mobilized to sustain themselves and continue their activities long after the immediate disaster abated. We contribute insights into the adaptation decisions of emergent organizations, guidance in understanding these decisions in relation to their social and historical context, and considerations for how long-term, network-oriented studies can help address some of the contemporary challenges in crisis-informatics research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".