Bibliographic record
Abstract
NATO was established in 1949 when the USA, Canada, and ten European states signed the North Atlantic Treaty. The treaty emphasized protecting the security of NATO members, primarily Western European countries, from threats posed by the Soviet Union. After the dissolution of the Soviet Union, NATO adopted a strategy of expansion, believing that increasing its membership would improve its effectiveness in safeguarding European security. NATO also recognized the significance of non-traditional threats such as instability, and terrorism outside its borders, which could potentially threaten the security of its members. As a result, NATO expanded its security concept to encompass political, economic, social, and environmental factors. Consequently, NATO began to address these new threats emerging outside the European continent, such as illegal immigration, counter-terrorism, and peacekeeping operations. NATO's involvement in Afghanistan from 2001 to 2014 marked the Alliance's first deployment outside Europe and its longest war to date. The mission ended with NATO's withdrawal from Afghanistan in 2014 after failing to achieve its objective of building a Western-style democratic state. However, NATO maintained a training and advisory mission until withdrawing it in 2021. My study aims to analyse the factors that led to NATO's failure in its mission in Afghanistan and its impact on the Alliance's willingness to undertake new missions outside Europe.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".