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Protection of Civilians

2023· book-chapter· en· W4387785324 on OpenAlexaboutno aff
Kseniya Oksamytna

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsnot available
Fundersnot available
KeywordsPeacekeepingPolitical sciencePersuasionPublic administrationCredibilityGovernment (linguistics)ShamePublic relationsLawPsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Many analyses look at protection of civilians in UN peacekeeping from 1999 onwards. However, the issue has a longer genealogy. There have been four advocacy episodes: an unsuccessful persuasion attempt by the Secretary-General during the 1960s mission in the Congo, incoherent advocacy by proponents of the ‘safe areas’ policy in Bosnia, a partially successful campaign by elected Security Council members during the Rwandan genocide, and successful persuasion by Canada during its 1999–2000 Council term. Focusing on the (partially) successful episodes, a coalition of elected Council members used a threat of shame to extract concessions from the permanent members to adopt a presidential statement critical of the Rwandan government. They faced a mix of advantageous conditions, including advocates’ reputation, post–Cold War unity, credibility of the private threat, and a cultural match, as well as inauspicious circumstances, such as high issue salience and targets’ counter-narratives. In 1999, Canada used persuasion to place protection of civilians on the Council’s agenda. Favourable circumstances included advocates’ skill, targets’ first-hand exposure to civilian suffering, a cultural match, repeated interactions, a crisis of peacekeeping, and a private setting. In 2010, the Secretariat produced a concept of protection of civilians, followed by policy and guidance. Missions nowadays have units or coordination forums on the issue, and the Protection of Civilians Team exists at headquarters. In the late 2010s, protection became a priority in several missions, yet contestation by traditional sceptics, such as Russia, as well as major troop contributors and UN officials, also intensified.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.918
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.073
GPT teacher head0.316
Teacher spread0.244 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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