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Record W4248525081 · doi:10.18192/potentia.v11i0.4611

“We are not getting the good stories out”: revisiting Quebec media coverage and NATO’s strategic narrative for the International Assistance and Security Force (ISAF)

2020· article· en· W4248525081 on OpenAlexaffvenueabout
Patricia Aya Dufour

Bibliographic record

VenuePotentia Journal of International Affairs · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsNarrativeStrategic communicationOpposition (politics)BlamePolitical sciencePublic relationsNewspaperPublic administrationSociologyLawPoliticsPsychology

Abstract

fetched live from OpenAlex

The purpose of NATO’s strategic communications is to inform and influence key audiences into supporting its decisions and operations. High levels of public opposition in contributing nations to NATO-led International Security Assistance Force (ISAF) in Afghanistan has led many to blame strategic communications for failing to explain the objectives and the importance of the mission. This paper seeks to evaluate where strategic communications succeeded and where they failed using Quebec as a case study, as it is the Canadian province that had the highest levels of opposition to the mission. The first part of this study uses NATO internal communications products to establish the core messages of the ISAF narrative in different phases of the mission. The second part surveys the main themes in the coverage of ISAF in Quebec’s main newspapers and TV shows. The major finding of this paper is that there was an effective dissemination of the NATO narrative in Quebec media, yet the narrative had little impact on opinion polls. The fact that the strategic communication campaign was successful in informing but not in influencing the Quebec audience carries important implications for the crafting of future NATO strategic narratives. This study concludes that efforts to improve military strategic communications in should focus developing communication products specific to minority cultures.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.031
GPT teacher head0.300
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2020
Admission routes3
Has abstractyes

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