Bibliographic record
Abstract
Bringing together the historical and the contemporary, the political and the personal, Disaster Memorials and Monuments: History, Context and Practice from around the World presents a wide-ranging understanding and exploration on memorials and monuments built in the aftermath of accidents, natural disasters and acts of violence. Disaster management expert, Kjell Brataas, provides a compassionate voice to difficult and complex situations as well as practical advice based on lessons learned through academic research, site visits and personal experience. Brataas illustrates a wide range of monuments and memorial projects from all over the world and explains the process of their creation and the challenges that occur in memorialization processes. He further proposes strategies for dealing with trials and controversies in similar future developments. Features include: Personal interviews with key stakeholders in the field of memorializing, psychology and victim support, who have first-hand experience with memorial projects Insights, lessons learned and advice from scholars, professors, politicians, support group leaders, survivors, bereaved, community leaders and neighbors Reporting on more than 80 memorials from around the world, including New Zealand, Canada, the United States, Sahara, Chile, Japan and South Korea Suggested reading, including books, reports and presentations on the topic Disaster Memorials and Monuments: History, Context and Practice from around the World is important reading for all practicing professionals, for those who study and teach the importance and the process of developing memorials and monuments and for everyone interested in crisis management and the aftermath of disasters.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".