Bibliographic record
Abstract
For much of the post 9/11 period, liberal jurists have resisted the entrenchment of radical measures and insisted upon the compatibility of freedom and security. Yet they have been largely ignored in a political climate in which fear and reaction dominate. This chapter argues that the nature of this impasse can best be understood in terms of the decline in the cultural currency of Ronald Dworkin’s concept of ‘rights as trumps.’ First argued in 1970, in a period of human rights ascendency, Dworkin’s approach rejected the notion of balancing individual and collective interests in favour of the moral priority of individual dignity and equality. Despite an increasing concern with security and risk in western law and politics, rights as trumps retained a degree of currency from the 70s to 2001. But 9/11 would radically undermine the ideal by altering our assumptions about the magnitude of the risk posed by criminal activity, and specifically in terms of what can be called the harbinger theory — a belief that 9/11 marked a new order of terror, with further attacks likely to occur on a similar or greater scale, possibly involving WMD. This chapter examines Dworkin’s defence of rights as trumps in light of this later imaginary to reveal its implied conditions and their complication by the harbinger theory. The demise of rights as trumps — and the larger impasse in current debates about rights and security — is seen here to be a consequence of an inability to reconcile the prospect of mass terror with earlier ideas about rights, risk, and security.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.077 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".