Institutionalisation of the Analytical Support Function to Ensure Credibility of Defence Management - Canada, Norway, Sweden and NATO Case Study
Bibliographic record
Abstract
The paper outlines several recommendations for strengthening the institutional framework of the analytical support function for credible defence management.Recommendations are drawn based on the outcome of the institutional research project named Strategic Alternatives conducted by the Centre for Security and Military Strategic Studies of University of Defence (CSMSS).The multi-objective research focuses on organisational arrangement of the analytical support function within the overall ministry of defence organisational architecture of several countries (Canada, Norway, Sweden) as well as the NATO structure and management (in this case, the main focus embraces the analytical support to defence planning). Abstrakt:Článek doporučuje některé přístupy pro posílení institucionálního rámce analytické podpory za účelem zvýšení důvěryhodnosti řízení obrany.Doporučení jsou výsledkem výzkumu, který byl proveden Centrem bezpečnostních a vojenskostrategických studií Univerzity obrany (CBVSS) v rámci dlouhodobého záměru rozvoje organizace s názvem Strategické alternativy (STRATAL).Výzkum byl zaměřen na organizační uspořádání funkce analytické podpory v rámci celkového organizačního uspořádání ministerstev obrany několika vybraných zemí (Kanada, Norsko a Švédsko) a v rámci organizační struktury NATO (v tomto případě byla pozornost zaměřena především na analytickou podporu obranného plánování).
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".