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Record W2786934533 · doi:10.5334/sta.606

Strategic Communications for Peace Operations: The African Union’s Information War Against al-Shabaab

2018· article· en· W2786934533 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 · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
FundersGeorge Washington University
KeywordsFunction (biology)Political scienceStrategic goalWageSoviet unionPublic relationsBusinessLawPoliticsMilitary science

Abstract

fetched live from OpenAlex

Despite widespread agreement that effective strategic communications are a necessary part of complex peace operations, many missions struggle to generate relevant capabilities and implement effective campaigns. This article analyzes the experiences of the African Union Mission in Somalia (AMISOM) as a case study of this problem. Specifically, it examines how the United Nations (UN) tried to fill the gap by hiring a consortium of private firms known as the AU-UN Information Support Team (IST) to wage a strategic communications campaign against al-Shabaab. The IST’s goal was to drive, as well as communicate, AMISOM’s success, improve the mission’s media presence, and develop a communications strategy. The IST played an innovative and important function for AMISOM but suffered from several significant challenges that reduced its effectiveness. The conclusion therefore identifies four main lessons from AMISOM’s experiences that could improve strategic communications for peace operations.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.055
GPT teacher head0.345
Teacher spread0.290 · 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