Bibliographic record
Abstract
Despite some harsh criticisms of United Nations (UN) peace operations, research demonstrates that many UN missions are successful, though evaluations depend on how success is defined. Even UN missions that fail in one or more aspects provide a net benefit to peace processes and help to save lives and alleviate human suffering. While an understanding of the flaws and limitations of peace operations can help improve the operations, some unfair criticism must be directly challenged. For instance, contrary to critiques in a recent paper by Séverine Autesserre, the UN has helped end civil wars, and it does not have a fixation on elections nor does it ignore the bottom-up approach. Most UN multidimensional missions pursue multiple levels of engagement, from local to national leaders. Elections are a key way to engage locals. With decades of experience, the UN has many positive lessons to offer in making, keeping, and building peace.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".