Bibliographic record
Abstract
The Human Security Report 2009/2010 argues that long-term trends are reducing the risks of both international and civil wars. The Report, which is funded by the governments of Canada, Norway, Sweden, Switzerland and the United Kingdom and will be published by Oxford University Press, also examines recent developments that suggest the world is becoming a more dangerous place. These include the following: --Four of the world's five deadliest conflicts--in Iraq, Afghanistan, Pakistan, and Somalia--involve Islamist insurgents. --Over a quarter of the conflicts that started between 2004 and 2008 have been associated with Islamist political violence. --In the post-Cold War period a greater percentage of the world 's countries have been involved in wars than at any time since the end of World War II. --Armed conflict numbers increased by 25 percent from 2003 to 2008 after declining for more than ten years. --Intercommunal and other conflicts that do not involve a government increased by more than 100 percent from 2007 to 2008. --The impact of the global economic crisis on developing countries risks generating political instability and increasing the risk of war. --Wars have become intractable--i.e., more difficult to bring to an end.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.082 |
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".