Resilient Disaster Recovery: A Critical Assessment of the 2006 Yogyakarta, Indonesia Earthquake using a Vulnerability, Resilience and Sustainable Livelihoods Framework
Bibliographic record
Abstract
Since the 2004 Indian Ocean tsunami devastated coastal areas of several countries in South East Asia, there has been renewed interest in disaster recovery operations. Although governments and aid organizations have increasingly focused on improving living conditions and reducing vulnerability to future disaster events during the recovery period, there has been limited understanding of what effective disaster recovery entails, and a lack of empirical assessments of longer-term recovery initiatives. Researchers, governments and aid organizations alike have increasingly identified the need for a systematic, independent, and replicable framework and approach for monitoring, evaluating and measuring the longer-term relief and recovery operations of major disaster events. \nWithin this context, the research contends that a conceptualization of effective disaster recovery, referred to as ‘resilient disaster recovery’, should be built upon the holistic concepts of vulnerability, resilience and sustainable livelihoods. Using the resilient disaster recovery framework, the research aimed to develop an evaluative strategy to holistically and critically assess disaster recovery efforts. Using a case study of the 2006 Yogyakarta, Indonesia earthquake event, the research examined one long-term recovery effort in order to develop and test the usefulness and applicability of the resilient disaster recovery conceptualization and assessment framework. The research results further contributed to disaster recovery knowledge and academic literature through a refined conceptualization of resilient disaster recovery and further understanding of recovery as a process. \nThe research used qualitative research approaches to examine the opinions and experiences of impacted individuals, households, and communities, as well as key government, academic and humanitarian stakeholders, in order to understand their perceptions of the long-term recovery process. Using the resilient disaster recovery approach, the research found that the recovery programming after the 2006 Yogyakarta earthquake contributed to reductions in visible manifestations of vulnerability, although the root causes of vulnerability were not addressed, and many villagers suffer from ongoing lack of access to assets and resources. While some aspects of resilience were improved, particularly through earthquake-resistant housing structures, resilience in other forms remained the same or decreased. Furthermore, livelihood initiatives did not appear to be successful due to a lack of a holistic approach that matched the skill and capital levels of impacted populations. \nUsing the evidence from the 2006 Yogyakarta recovery effort, the research furthered knowledge and understanding of disaster recovery as a complex and highly dynamic process. The roles of a variety of actors and stakeholders were explored, particularly highlighting the role of civil society and the private sector in facilitating response and recovery. Furthermore, issues of conflict, the context and characteristics of place and scale, and the impact of disasters on income equality were explored. Through this research, an improved understanding of disaster resilient recovery and long-term recovery processes has been highlighted in order to facilitate improved and resilient recovery for future disaster events.
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 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".