Bibliographic record
Abstract
This chapter for the Oxford Handbook of Criminal Process offers a critical, comparative account of pretrial evidence disclosure laws in common law jurisdictions. Disclosure law was once minimal throughout the common law world; the longstanding norm was that one party need not aid the other’s preparation by sharing evidence prior to trial. Substantial pretrial disclosure duties are comparatively recent, and reflect several developments. One is the fact that trials are now exceptional as the process by which to resolve prosecutions; guilty pleas are the norm. Evidence can face adversarial scrutiny, and facilitate negotiated resolutions, only if parties have pretrial access to it. Another is changes in the nature of evidence; expert analysis, for example, often cannot be confronted effectively without advance preparation. Moreover, pretrial disclosure has gradually become understood to make both trials and negotiated resolutions more efficient, and — despite some dissent — to improve the truth-finding capacity and fairness of criminal process. Common law jurisdictions show considerable similarity on disclosure rules. In the last half century, there emerged a strong consensus that the government must disclose relevant evidence in its possession that does not support the prosecution’s case and thus that it would not present at trial. Rules also typically impose greater duties on the defense to disclose significant portions of its evidence before trial. The critical exception to this international consensus relates to inculpatory evidence. Rules in England, Canada, and elsewhere outside the United States generally require the prosecution to disclose evidence it will rely on to prove guilt. Many U.S. jurisdictions, however, have resisted this trend, mandate very little prosecution disclosure, and even limit judicial authority to compel such disclosure. As a framework for critical assessment, the chapter examines structural choices that adversarial justice systems must make in disclosure schemes and their rationales doing so. Those choices include how much to empower judges rather than parties to control disclosure, and how to enforce parties’ obligations to disclose when their partisan interest counsels otherwise. Those decisions reflect assessments about how to balance competing epistemic and non-epistemic goals including the goal of accurate truth-determination and divergent interests of the parties, constitutional principles, and the security or privacy victims and witnesses.
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 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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".