Why have there been no more ‘affairs’ like Somalia, Rwanda and Srebrenica?
Bibliographic record
Abstract
Klep, Christ, Somalië, Rwanda, Srebrenica. De nasleep van drie ontspoorde vredesmissies (Dissertatie Utrecht 2008; Amsterdam: Boom, 2008, 385 blz., ISBN 978 90 8506 668 2) In his dissertation, Dr. Klep concentrates on peace operations and their aftermath as fairly domestic matters in Canada, Belgium and the Netherlands. These three peace operations also fit, however, into an international development at the end of the Cold War. Classic, ‘blue’ peacekeeping was largely replaced by more robust ‘green’ international interventions that are not only more dangerous, but during which much more is expected of the peacekeeping forces. New ‘affairs’ surrounding peace operations have not occurred. The un and national governments are less inclined to begin such missions (namely Daurfur). Presumably the armed forces of several countries have drawn lessons from the peace operations that went off the rails. Also the public is less shocked by accusations of misconduct under difficult circumstances. This review is part of the discussion forum 'Somalië, Rwanda, Srebrenica' (Christ Klep).
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".