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Record W2118816954 · doi:10.5334/sta.dw

Surviving Violence: Transgressing Categories and Boundaries in Armed Conflicts

2014· article· en· W2118816954 on OpenAlex
Carla Suárez, David Black

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueStability International Journal of Security and Development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPeacekeepingScrutinyGlobePolitical scienceHuman rightsHarmTerrorismArmed conflictSmall armsLawCriminologyPublic relationsSociologyPsychologyBusinessInternational trade

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.295
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it