Bibliographic record
Abstract
Gender-based Violence (GBV) is costly, from a human, psychological, and economic point of view. It is estimated to represent worldwide a loss equivalent to Canada's GDP (1.5 trillion dollars). This loss is seen but not heard. GBV has taken the lives of over 200 million women worldwide, comparable in number to the population of Brazil, Pakistan, or Nigeria. GBV has destroyed the lives of millions of women and girls, who are survivors of this everyday violence. In this respect, GBV again is seen but not heard. In this speech Sandie Okoro, the General Counsel of the World Bank, reflected on her personal experience as a female international lawyer and on her journey toward achieving recognition and leadership in her field. She presented the life stories of courageous and inspirational women on every continent who have suffered extreme violence, yet who have persevered and fought ferociously for the rights of other women who suffer a similar plight. The focus was on women who have employed their efforts toward shaping and influencing the direction of international law and national jurisprudence so they can be seen and heard. Sandie's speech also homed in on the fragmentation that exists with respect to women's rights, both in terms of enforcement and implementation. She illustrated the fact that even in instances where laws tackling GBV or gender inequality exist, in certain contexts there are still severe gaps in their application. It is indisputable that the agenda to combat GBV is of paramount importance. Yet the question remains as to what our individual and collective roles in this regard ought to be. It is incumbent upon us, the legal community at large, to ensure that it is both seen and heard from this point on.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.466 | 0.236 |
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".