Bibliographic record
Abstract
In Mexico, increasing demands for public safety coupled with the need for a more effective criminal justice system resulted in the security and justice constitutional reform of 2008. The outcome was a constitutional framework with provisions based on the highest standards of human rights on the one hand, and on the other, exceptional measures that restrict rights in an attempt to improve public safety. Unfortunately, the crime rate and incidence of unreported crime have changed little. When public safety is demanded, a clear, rational and concrete response is required. Limiting the alternatives to pre-trial detention or increasing penalties is rarely the appropriate response. This paper focuses on pre-trial detention and non-custodial measures supported by the new criminal justice system, how they relate to the principle of the presumption of innocence and the tension between this and the punitive demands for increased imprisonment. In addition, this study discusses a technical solution, found in pre-trial services, which seeks to balance the presumption of innocence and the right to personal liberty with public safety.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.053 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.010 | 0.010 |
| 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".