Learning Lessons (And How) in the War on Terror: The Canadian Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
LEARNING LESSONS IS AN UBIQUITOUS URGE. Armies do it; international organizations such as the United Nations practice it; businesses engage in it; individuals rely on it to get on with life. The internet teems with examples of our appetite. Casual perusal of the amazon.com books site reveals thousands of current titles on learning lessons, spanning everything from business guides to success, to learning from nature and even, sadly, one's pets. The list speaks to a societal activity that seems both frenetic and routine.Yet in the world of security and intelligence, the practice of learning lessons has typically been viewed as more problematic. Resistance is generated by a host of factors, some unique to the culture of security and intelligence agencies. Internal exercises in learning lessons can be resource intensive, and therefore low in priority. They rarely have an obvious bureaucratic home, especially in decentralized systems, and can involve painful processes of self-criticism. They are seen as difficult to translate into practical, sustained measures. Perhaps most important, they cut against the grain of an intensive focus on current operations and forward-looking strategic assessments. To be willing to engage in learning lessons, security and intelligence communities have to be prepared to value the past, and to believe that there are important lessons to be learned from history. Such beliefs are rare. To add to the friction, externally generated exercises in learning lessons are often perceived by security and intelligence communities not just as diversions from important ongoing requirements but as exercises in scapegoating, coming as they usually do on the heels of scandal and failure. This only reinforces a reluctance to engage in an analysis of past performance and can create a climate in which failure or weakness is always cast off as an orphan.But the events of 11 September 2001 and the Iraq war have rocked the foundations of the world of intelligence. The enormity of the intelligence and policy failures that characterized both the al Qaeda strikes of 11 September and the origin and conduct of the war in Iraq have had two significant side-effects. One is the onset of a crisis of public confidence in security and intelligence services, along with enormous confusion about where the boundaries between intelligence and policymaking do and should lie. The reputation of intelligence services has been laid low, perhaps lower than at any previous moment in their modern history.An equally powerful side-effect of these recent events has been an enhanced desire and demand for greater transparency and accountability. In an age of counterterrorism and global preemption, where much rides on intelligence services getting it right, and where expanded government powers raise natural anxieties about threats to civil liberties, citizens want to know more, profoundly more, about hitherto secret or secretive institutions of the state.In the context of these twin effects-rock bottom confidence and greater public assertiveness-the practice of learning lessons takes on new meaning and gravity. Craig Whitney of the New York Times, in his introduction to an edition of the 9/11 commission report, gave efforts to learn lessons in the public domain a high calling: demanding accountability from the elected and appointed officials of government, and insisting on revealing and correcting their shortcomings, are the most basic rights and duties of citizens in a democracy.1The US 9/11 commission report is only one, albeit the most famous, of a spate of high-level reviews and inquiries into the performance of security and intelligence agencies that have flourished in a variety of countries since September 11. In addition to an intensive effort in the United States, the United Kingdom, Australia, and Israel have all embarked on significant public efforts to learn lessons about the failures of intelligence since September 11. …
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it