Victims’ rights are human rights: The importance of recognizing victims as persons
Bibliographic record
Abstract
In this paper the author argues that victims’ rights are human rights. Criminal law typically views victims as witnesses to a crime against the state, thus shutting them out of the criminal justice process and only allowing them in when they are needed to testify. This is a major source of dissatisfaction for victims who seek validation in the criminal justice system. Victims are persons with rights and privileges. Crimes constitute violations of their rights as well as acts against society or the state. While human rights instruments, such as the Universal Declaration of Human Rights, do not mention crime victims specifically, a number of rights are identified, which can be viewed from the victim’s perspective. As individuals with dignity, victims have the right to recognition as persons before the law. However, such rights are only meaningful if they can be enforced.
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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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.060 |
| Scholarly communication | 0.013 | 0.025 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".