MétaCan
Menu
Back to cohort
Record W2135980032 · doi:10.5334/sta.bo

In the Eye of the Beholder? The UN and the Use of Drones to Protect Civilians

2013· article· en· W2135980032 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStability International Journal of Security and Development · 2013
Typearticle
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPeacekeepingDroneInternational humanitarian lawPolitical scienceObligationHuman rightsSituation awarenessDemocracyLawComputer securityBusinessPoliticsEngineeringComputer science

Abstract

fetched live from OpenAlex

The debate on the UN’s possible use of drones for peacekeeping took a turn in 2013 when the Security Council granted the Department of Peacekeeping Operations (DPKO) permission to contract surveillance drones for MONUSCO, its peacekeeping mission in the Democratic Republic of Congo (DRC).<br />This article examines what drone capability may entail for UN peacekeeping missions. We find that surveillance drones can help missions acquire better information and improve the situational awareness of its troops, as well as inform decision-making by leadership, police, and civilian components of the mission. We see a significant potential in the use of surveillance drones to improve efforts to protect civilians, increase UN troops’ situational awareness, and improve access to vulnerable populations in high-risk theaters. The use of drones can dramatically improve information-gathering capacities in proximity to populations at risk, thereby strengthening the ability of peacekeepers to monitor and respond to human rights abuses as well as violations of international humanitarian law (IHL). Drones may also enable peacekeepers to maintain stealth surveillance of potential spoilers, including arms smugglers and embargo breakers. They could additionally improve UN forces’ own targeting practices, further contributing to the protection of civilians (PoC). Furthermore, we emphasize how drone capability significantly increases peacekeepers’ precautionary obligations under IHL in targeting situations: the availability of drones triggers the obligation to use them to gather information in order to avoid civilian casualties or other violations of IHL or international human rights law.<br />There may soon come a shift among human rights groups, from being skeptical of the use of drones by UN peacekeepers to demanding that peacekeeping operations be equipped with surveillance drones for humanitarian and human rights reasons – shifting the current debate, which has focused largely on the negative impact of the use of drones, to a more balanced debate that considers more objectively what drones are and what they can be used for. Finally, the debate about armed drones looms on the horizon for the UN as well – and we outline some of the key dilemmas that the inclusion of such a capability will entail.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.117

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.208
Teacher spread0.190 · 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