Bibliographic record
Abstract
The co-defendant refers to defendants that get involved in the same criminal procedure and the merger investigation, prosecution and trial, or any other defendants who share implicated relationship due to additional prosecution. In practice, there is a problem that whether the defendant can motion the exclusionary rule of the illegally obtained co-defendant confession. Even though the current exclusionary rule had positive improvement in these years, there are still blank areas, among which the problem doesn’t get a clear answer in the legislation. The question contains a preposed key point: how to define the character of co-defendant confession? Regarding that the part of the co-defendant confession about other co-defendants is often an important and unfavorable evidence against them, from the perspective of a fair trial, this confession should be regarded as witness testimony against other co-defendants. And it is necessary to give other defendants the right of cross-examination. For the purpose of deterring and curbing the state organs from illegal investigation in criminal proceedings, the accused should be fully given the qualification to motion the exclusionary rule within a reasonable range. Therefore, based on the intrinsic attribute of witness testimony in the co-defendant confession, the defendant should be entitled to the right to motion, if and only if the part of the co-defendant confession related to him is obtained by illegal torture.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".