Bibliographic record
Abstract
In seeking to present itself as a peace nation, Norway must address often the awkward questions of its military activism and NATO membership. This tension was especially apparent in Norway’s campaign for a seat on the UN Security Council 2020–2021. Using nation branding as an analytical framework, we ask how Norway, when vying for this seat, built and sustained this peace narrative and managed the competing narrative of its militarism. We also ask how Norway’s two competitors, Ireland and Canada, presented themselves on these two axes of peace and military activism. To explore these questions, we analyse campaign-related speeches and texts from Norwegian officials, together with the official campaign material from all three countries. Given that the image of all three states was generally similar, each country sought to find unique ways to brand themselves as well as countering the few specific advantages of the others. For Norway, the country’s military activism was downplayed and gender equality and international development cooperation were foregrounded, even if the links with security and peace were at times strained. Such a narrative would legitimate sufficiently the idea of Norway as a peace nation, a reliable partner that all states could trust.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".