Bibliographic record
Abstract
The national security and intelligence advisor to the prime minister (NSIA) is one of the most important officials in the Canadian government. The NSIA counsels the prime minister on critical matters of national interest while coordinating a complex security and intelligence community and engaging relevant actors worldwide. The significance of the office has ebbed and flowed over the decades, depending on the individual in the job, the interest of the prime minister and the state of the world. As the definition of national security has expanded and the world has become more unsettled, the position has become increasingly complex and demanding. This paper examines the evolution of the office over the years, the officials who have held the job and the ways in which they collaborated with their colleagues across government to address emerging threats, while also touching upon many of the security-related events that grabbed the headlines during these years. At a time when threats to Canada are more serious than ever and our closest allies are no longer inherently trustworthy, a complacent attitude toward national security cannot be tolerated. Exploring the history of the NSIA and identifying ways to improve the office in the future may help Canada chart a path forward in a dangerous world.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.014 |
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".