Unthinking Extremism: Britain's Fusion Intelligence Complex and the Radicalizing Narratives that Legitimize Surveillance
Bibliographic record
Abstract
The aim of this paper is to examine how Britain's Public Authorities and private investors alike have come to define common activists as terrorists, using a range of security methods that have gained surprising ground during the past decade. In short, newfound terms such as "extremism" have been popularised to condemn the activities of groups such as al Qaeda and ISIS (Islamic State), but at the same time have been applied to campaigners for the 'far less politically correct deterrence of dissenting public discourse' (Leman-Langlois, 2009). This paper therefore argues that with the application of terms such as "extremists" to Britain's campaigners, these signifiers have notably radicalized protest groups - not by virtue of their actions per se[1], but by way of the very deliberate repositioning of activists within national security and counter-terrorism frameworks. Nevertheless, it should be recognised that while such narratives are being disseminated at both a national and regional level in the UK, they also form part of a wider Strategic Dialogue, which occurs throughout the West[2]. Indeed the ultimately aim of such practices is to criminalize all forms of extremism (including public acts of direct action), for their capacity to incite civil unrest. Fundamentally speaking, while significant work has been undertaken by leading academics from Europe, Canada, and the USA, relatively little is known about Britain's fusion intelligence centres, in which case the following paper aims to make a valuable contribution to this emerging trend in the policing of domestic affairs, by highlighting the operational protocols and legitimizing narratives that are in use today.[1] Though the strategic dissemination of this dialogue, forms part of an overall campaign to reduce popular sympathy for demonstrators.[2] See the Institute for Strategic Dialogue (ISD), regarding the international mobilization of counter-terrorism/ extremism narratives.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".