Managing national security and law enforcement intelligence in a globalised world
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
Abstract This article argues that there are five major challenges currently facing Western intelligence communities. First – ensuring skills retention for intelligence officers and analysts, while developing knowledgeable managers and customers, all in an increasingly-complex security environment. Second – instituting and inculcating knowledge and expertise in these staff – while addressing an opponent in al-Qaeda which demonstrates increasingly sophisticated use of IT, new media, etc. Third – drawing-in outside expertise from the research and business communities, as is done currently in the US and Canada but in only a very limited manner in the UK. Fourth – overcoming institutional rigidity in dividing the foreign and domestic – alongside rigid sharing and co-operation relationships. Fifth – creating truly collaborative environments that offer genuine socio-cultural incentives to collaboration rather than mere ‘IT solutions’.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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