La mediación en violencia intrafamiliar: modelos internacionales, efectividad y constitucionalidad en el contexto ecuatoriano
Bibliographic record
Abstract
Domestic violence is a serious human rights problem that affects women, children and other vulnerable family members around the world. In Ecuador, this type of violence includes not only physical aggression, but also emotional and economic control and psychological manipulation. Where 65% of women have been victims of some type of violence throughout their lives. The effects of domestic violence are profound, affecting the physical and mental health of victims, who often suffer injuries, chronic illnesses, anxiety, depression and post-traumatic stress. In addition, they face social isolation and difficulties in achieving economic independence, which perpetuates their dependence on the aggressor. To address this problem, Ecuador approved in 2018 the Comprehensive Organic Law to Prevent and Eradicate Violence against Women, which establishes protection measures and sanctions against aggressors. However, the implementation of this legislation faces obstacles, such as lack of resources and gender stereotypes that view domestic violence as a private matter. Mediation has emerged as an alternative to resolve conflicts in cases of domestic violence in several countries, although its use is controversial due to power imbalances between the parties. In places such as Canada and Norway, it has been implemented under strict conditions to protect victims. In Ecuador, any proposal to incorporate mediation must focus on guaranteeing the safety and rights of victims, avoiding their re-victimization and ensuring an approach based on human rights and gender equity.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".