Artefacts of disaster risk reduction: conceptualizing bottom-up initiatives of climate action in informal settlements
Bibliographic record
Abstract
Purpose Disaster risk reduction is of prime importance in informal settlements in the Global South, where several forms of vulnerability coexist. Policy and official programmes, however, rarely respond to the needs and expectations of citizens and local leaders living in these settlements. Even though these agents constantly attempt to reduce risks in their own way, we know very little about their activities, motivations and effective impact on risk reduction. Here we seek to conceptualize bottom-up initiatives to better grasp their origins, limitations and success. Design/methodology/approach Through a four-year action-research project in Colombia, Cuba and Chile, we theorize about the production of change by local agents. Through detailed case studies we explored the activism of 17 local leaders. Through narrative analysis we studied their motivations and explanations. Finally, by documenting 22 initiatives, we revealed effective changes in space. Findings In the face of risk and disasters, residents and leaders in informal settings engaged in symbolic, physical and social spaces of interaction. Their actions were guided by trust, emotions, time cycles and activism. Local agency was justified by narratives about risk and climate change that differ from those of authorities and scholars. Research limitations/implications There is still limited understanding of bottom-up initiatives in informal settings. It is crucial to conceptualize their origins, limitations and success. The focus on three specific countries necessitates further research for broader applicability and understanding. Practical implications A better comprehension of bottom-up actions is crucial for informing policies and programmes aimed at reducing risk in informal settings. Stakeholders must recognize the political, social and cultural roles of these actions for more impactful climate action. Originality/value We borrow Simon’s concept of “artefact” to introduce the notion of “Artefacts of Disaster Risk Reduction”, providing insights into the multifaceted nature of bottom-up initiatives. We also emphasize the simultaneous political and phenomenological character of these actions, contributing to a deeper understanding of their origins and impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".