Bibliographic record
Abstract
This book examines the various ways in which Africa has been implicated in the politics and practices of security since 11 September 2001. It focuses on the effects and outcomes of American policy and security discourses (from George W. Bush to Barack Obama) on the people and states of Africa by exploring the links between terrorism, the ‘war on terror’, democracy, human rights, and diverse security practices of the post-9/11 world order. One of the key objectives of the collection is to ‘foreground knowledge that is local, subaltern and from peripheral regions; that is discontinuous and disruptive to progressive notions of history; and that may even be characterized as “illegitimate” from the standpoint of conventional terrorism studies’ (p. xvi). The book begins with a substantial and provocative essay written by the editor in which she deconstructs and exposes the effects of ‘terrorism thinking’. For Smith, the production of knowledge associated with ‘terrorism’ is a central issue. The fact that ‘an event in a metropolitan center is established as world transformative’ can only be called into question when it is compared to alternative claims or narratives from the periphery (p. 17). An analysis of post-9/11 discourses on terrorism from marginalized perspectives is a strategy that ‘exposes the normative implications of the production of hegemonic voice and stories about political violence and terrorism’ (p. 17).
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".