The architecture of community: Intelligence community management in Australia, Canada and New Zealand
Bibliographic record
Abstract
While many have examined individual intelligence agencies and cooperation between agencies bilaterally, the study of the interdepartmental architecture that is meant to coordinate intelligence communities has been peripheral at best. This is especially true in the case of smaller states, such as Australia, Canada and New Zealand. However, this architecture is fundamentally important to our understanding of how the secret state operates; how it impacts, and is impacted by, the open state; and, when taken comparatively, is indicative of differing government cultures towards intelligence. Examination of the development of intelligence community management architecture in Australia, Canada and New Zealand reveals that actors in all three communities recognise networks of interdependency between them. However the extent to which they are able to exploit these interdependencies is dependent on larger dynamics in government, supporting the idea that intelligence communities can only be as cohesive as the governments they serve allow them to be.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".