Bibliographic record
Abstract
This article describes the police intelligence division-of-labour. It is argued that police organisation gains overall coherence in relation to the ‘police métier’; a rationale that allows protagonists in the police world to make sense of an irrational workplace structure where personal loyalty, trust and honour (not formal organisational logic) form the basis of action and compliance. The concept of the police métier is defined in terms of the police professional concern with the mastery of surveillance and coercion in the reproduction of order, the making of crime and the governance of insecurity, and it is the polestar of the police mindset. The article describes the police intelligence division-of-labour paying specific attention to four different aspects of intelligence activity: the acquisition of intelligence or information; the analysis of information in the production of intelligence; tasking and co-ordination on the basis of intelligence ‘product’; or being tasked on that same basis. The descriptive analysis presented here is useful in several respects. Firstly it provides a basis for the comparative study of police intelligence work and its configuration within broader processes of security governance. Secondly, it provides a prototypical organisational map useful understanding the orientation of particular units – the organisational elements of policework (e.g. of drug squads, primary response, public order and homicide investigation units) – within the broader police division-of-labour. Lastly, it provides a complex view of issues concerning democratic governance of ‘the police’ as they are configured as nodes within broader networks of security governance.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".