Bibliographic record
Abstract
Today, cyber security, cyber defense, information warfare and cyber warfare issues are among the most relevant topics both at the national and international level. All the major states of the world are facing cyber threats and trying to understand how cyberspace could be used to increase power.Through an empirical, conceptual and theoretical approach, Cyber Conflict has been written by researchers and experts in the fields of cyber security, cyber defense and information warfare. It aims to analyze the processes of information warfare and cyber warfare through historical, operational and strategic perspectives of cyber attack. It is original in its delivery because of its multidisciplinary approach within an international framework, with studies dedicated to different states Canada, Cuba, France, Greece, Italy, Japan, Singapore, Slovenia and South Africa describing the states application of information warfare principles both in terms of global development and local usage and examples.Contents1. Canadas Cyber Security Policy: a Tortuous Path Toward a Cyber Security Strategy, Hugo Loiseau and Lina Lemay.2. Cuba: Towards an Active Cyber-defense, Daniel Ventre.3. French Perspectives on Cyber-conflict, Daniel Ventre.4. Digital Sparta: Information Operations and Cyber-warfare in Greece, Joseph Fitsanakis.5. Moving Toward an Italian Cyber Defense and Security Strategy, Stefania Ducci.6. Cyberspace in Japans New Defense Strategy, Daniel Ventre.7. Singapores Encounter with Information Warfare: Filtering Electronic Globalization and Military Enhancements, Alan Chong.8. A Slovenian Perspective on Cyber Warfare, Gorazd Praprotnik, Iztok Podbregar, Igor Bernik and Bojan Ticar.9. A South African Perspective on Information Warfare and Cyber Warfare, Brett van Niekerk and Manoj Maharaj.10. Conclusion, Daniel Ventre
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.013 | 0.028 |
| Scholarly communication | 0.024 | 0.017 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 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".