“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)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".