Defining Natural Hazards – Large Scale Hazards
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The natural forces at work on planet Earth have been an integral part of life since the dawn of mankind. The impacts of hazards of natural origin can range from affecting infrastructure, personal possessions, and ecosystems to negatively affecting individuals’ psychosocial wellbeing. Disasters are the aftermath of hazards caused by natural phenomena, set off by shifts in tectonic plates or atmospheric interactions in populated areas. The extant literature offers a variety of ways to classify natural hazards. For example, they can be categorized by their origin – geological, hydrometeorological or biophysical; by their nature and speed – permanent, ephemeral or episodic; or on the basis of their size or scale – large, medium or small. Adopting the last of the three classification schemes, this chapter presents large scale hazards, which are more likely to occur on the North American continent, in alphabetical order. The list of hazards includes biophysical hazards, droughts, earthquakes, extreme weather, floods, forest fires, ice storms and hurricanes. To help readers follow the material, the chapter draws heavily on recent examples.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it