Non-traditional security in the post-Cold War era : implications of a broadened security agenda for the militaries of Canada and Australia
Bibliographic record
Abstract
The growing salience of non-traditional security concerns for the post-Cold War national security of western states has led this author to ask: What implications does the post-Cold War proliferation of “security” threats, and therefore, the securitization of non-traditional challenges, hold for the primary security institution of the state, namely, the military? Using the research design of a heuristic case study, this project seeks to answer this question through the methodology of process tracing, relying on document analysis and semi-structured elite interviews for data. This dissertation first argues that the category of “non-traditional” security concerns can be separated into three “types”: (1) Fragile and Failing States, (2) Global Terrorism, and (3) Transnational Political Challenges. Using this framework, the dissertation then examines two cases, which are the national security strategies of Canada and Australia throughout the post-Cold War Era. For each case, the impact of the securitization of non-traditional security concerns is analyzed with relation to defence policy, military doctrine, force structure, and operational outputs. It concludes that both militaries have been significantly impacted by the securitization of non-traditional security concerns during the post-Cold War Era, although the securitization processes and policy outcomes have been different in each case.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".