Security in the West: Evolution of a Concept
Bibliographic record
Abstract
Since its appearance on the world stage, the West (Europe, the United States and Canada, Australia and New Zealand) has been a primary producer of security (for itself) and of insecurity (for itself and for others). Western discourse has not only invented the term security but also expanded and reshaped it according to its own complex evolution. The goals of this volume are to analyze the evolution of the contested concept of security and to discuss how the concept of security has emerged as a “Western social enterprise”. How Western conceptions of security have developed and changed since the end of the Cold War, the nature of new security challenges and their implications for the West and the direction in which evolving concepts of security will lead the West and the entire global community are some of the relevant themes addressed by contributors to this volume. \nThe manuscript emphasizes scholarly originality, methodological rigor and research. The audience for the book will be scholars and practitioners working in the field of international security, international relations students and as well as policy-makers with interests in the areas of national security. \nSecurity in the West can be adopted as a reader in undergraduate and graduate level courses addressing the security problem, or as recommended reading for disciplines such as world politics, international relations, globalization studies, security and public policy and others.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".