The game changes: "Disaster Prevention and Management" after a quarter of a century
Bibliographic record
Abstract
Purpose – This paper has been written to mark the 25th anniversary of the founding of Disaster Prevention and Management. It reviews the modern-day challenges facing researchers, scholars and practitioners who work in the field of disaster risk reduction. Design/methodology/approach – The paper reviews key issues in disaster risk reduction, including the relationship between capital and labour and its influence on vulnerability, the role of human mobility and migration in disaster vulnerability and the definition of welfare. Findings – There is a need for a major revision in the body of disaster theory so that it can take account dynamic changes in the modern world. In the future, climate change and migration may radically alter the bases of vulnerability, risk and impact. The ways in which this will occur are not yet clear, but indications can be gained from current trends and the state of foment in which the world presently exists. Research limitations/implications – Prediction of future developments is always subject to the caveat that unexpected influences may change the expected course of events. However, we need to anticipate developments in order to produce theory, policies, and practical solutions that are well-thought-out and viable. Practical implications – Disaster theory must adapt to new conditions if it is to remain the "road-map" that clarifies complex realities and enables disasters to be managed and abated. Social implications – Huge changes in the stability, expectations and vulnerabilities of populations are underway. These need to be understood much more fully in terms of their ability to influence disaster risks and impacts. Originality/value – Presently, few analyses of the dynamism of global society are able to present a clear picture of the future needs of theory generation, scholarship and research.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".