G<scp>regory</scp> S. K<scp>ealey</scp>. <i>Spying on Canadians: The Royal Canadian Mounted Police Security Service and the Origins of the Long Cold War</i>.
Bibliographic record
Abstract
Gregory Kealey is one of a small number of academics conducting studies of the Canadian intelligence community. His focus is on security intelligence, often in the context of labor history, and his new book, Spying on Canadians: The Royal Canadian Mounted Police Security Service and the Origins of the Long Cold War, is a collection of essays prepared over the years following 1988, capturing the “tortured history” of the RCMP Security Service (RCMP SS). While the essays in the collection have been published elsewhere as articles or book chapters between 1988 and 2003, together the essays nevertheless capture much of the critical history of Canadian security intelligence prior to the creation of the Canadian Security Intelligence Service (CSIS), the civilian successor to the RCMP SS, albeit with some repetition of details. Security intelligence, or national security, is a complex task balancing protection of the nation with the rights and entitlements of citizens of the nation. In Canada’s case this did not always work in favor of the citizenry. Since the beginning of security intelligence activities in Canada, the focus has too often been on domestic constitutional political activity, albeit outside the conservative framework of the political establishment. It has been used as a tool to counter threats to mainstream political views. External national security threats were largely ignored until the onset of the Cold War (except for Fenians in the late 1800s).
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.245 | 0.085 |
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".