Surviving Violence: Transgressing Categories and Boundaries in Armed Conflicts
Bibliographic record
Abstract
Since the early 1990s, activities intended for the protection of civilians have been steadily incorporated into humanitarian, peacekeeping, and development operations across the globe. Yet, what was initially perceived as a progressive step in the advancement of human security (Goldberg and Hubert 2001) is now coming under increasing scrutiny (Fox 2002; Thakur 2002). The civilian protection agenda involves a series of inter-related activities designed to prevent, mitigate, respond to, and recover from physical harm caused by armed conflict. Despite the steady elaboration and execution of this agenda, however, critics point to key challenges including the lack of compliance by states and non-state armed actors (Ferris 2011), problems with coordination and efficiency among aid organizations (Barnett 2009), under-resourced peacekeeping operations with limited training and equipment (Williams 2013), and the lack of capacity and will on the part of the ‘international community’ (Barr 2010).
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.010 | 0.043 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".