A Study of Interaction Between Network Opinion and Judicial Progress: Perspective From Judgments of Several Criminal Cases
Bibliographic record
Abstract
Nowadays the network opinion, to some extent, represents appeals of the public to the pursuit of social justice, playing an utmost impact on judicial trials. Whereas network is sentimental and also with the features of virtuality and undiscipline and lack of rigorous procedures and the like, which can not intervene or even replace the normal functional progress of the judiciary trial which is very separate from other social activities. Network opinion plays an important role in promoting the realization of social justice, and also an imperative role in the supervision of judicial trials. The independence of judicial trials should not be surrendered due to the impact of network opinion. And the judicial trial should be open to cater to the need of the public, subject to the voice of the public on procedural fairness and disclosure by facing the network opinion in a correct way and accepting its supervision, to make each of the judged cases fair and square as time goes on. A combination of lawful effect and social effect will also be achieved as a whole with the guidance of judicial justice as the unique dominating value.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".