The Rule Against Admitting Exculpatory Statements of Accused Persons: A Shiny Coin That has Lost its Currency
Bibliographic record
Abstract
As a general rule, accused persons on trial in Anglo–North American criminal legal systems are not allowed to introduce into evidence exculpatory statements they have made out of court. There is no coherent rationale for this rule, which is difficult to defend as a matter of principle and pragmatism. Yet this "anomalous" rule1 remains alive and well, at least in the U.S.A. and Canada, and invariably becomes the focus of pretrial or midtrial argument in those cases where such statements have been made. When an accused person fails to convince a trial judge to hear or receive evidence that he or she made exculpatory statements out of court, trial fairness is typically jeopardized. This article contends that at least three overarching principles of criminal justice—the inclusionary principle of evidence, trial fairness, and the presumption of innocence—require the rule itself to be abandoned. It should also be rejected as a matter of practicality.
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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 | 0.083 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.068 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.039 | 0.046 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".