Bibliographic record
Abstract
Abstract This chapter examines the distinct operational and ethical challenges that prosecutors face in national security and especially terrorism cases. The second part of this chapter focuses on the operational challenges that prosecutors face. These include demands for specialization that may be difficult to fulfill given the relative rarity of national security prosecutions; the availability of special investigative powers not normally available in other criminal cases; exceptionally broad and complex offenses; and the demands of federalism and international cooperation. The third part examines ethical and normative challenges that run throughout the many operational aspects of the prosecutorial role in national security cases. These include the challenges of ensuring that often exceptional national security laws are enforced in a manner consistent with the rule of law and human rights. There are also challenges of maintaining an appropriate balance between legitimate claims of secrecy and legitimate demands for disclosure and between maintaining prosecutorial independence and discretion while recognizing the whole of government and whole of society effects of the many difficult decisions that prosecutors must make in national security cases.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".