National security, surveillance and terror: Canada and Australia in comparative perspective
Bibliographic record
Abstract
This edited collection brings together leading scholars to comparatively investigate national security, surveillance and terror in the early 21st century in two major western jurisdictions, Canada and Australia. Observing that much debate about these topics is dominated by US and UK perspectives, the volume provides penetrating analysis of national security and surveillance practices in two under-studied countries that reveals critical insights into current trends. Written by a wide range of experts in their respective fields, this book addresses a fascinating array of timely questions about the relationship among national security, privacy and terror in the two countries and beyond. Chapters include critical assessments of topics such as: National Security Intelligence Collection since 9/11, The Border as Checkpoint in an Age of Hemispheric Security and Surveillance, Unmanned Aerial Vehicles and Law Enforcement, as well as Federal Government Departments and Security Regimes. An engaging and empirically driven study, this collection will be of great interest to scholars of security and surveillance studies, policing, and comparative criminology.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".