Bibliographic record
Abstract
The emerging violence was not only against members of the political opposition, but there was also growing evidence of Hutu extremism against the Tutsi minority. The human rights violations ranged from hate propaganda to discrimination, violence and killings of Tutsi and moderate Hutu. It is important to note that in spring 1992 the bystander-states Canada, the United States, France, Belgium and the non-governmental organizations (NGOs) Amnesty International put the killings of the Tutsis in Rwanda on their agenda and held the Rwandan government responsible and accountable for these atrocities. Bacre Waly Ndiaye, who was the U.N. Special Rapporteur on Extrajudicial, Summary or Arbitrary Executions, talked explicitly about a tpossible genocidet Integral parts of the hate propaganda against the Tutsi minority were the hate-citing radio broadcasts and newspaper articles. One has observed many very clear early warnings from divergent sources.Keywords: bystander states; early warnings; extrajudicial executions; hate propaganda; human rights organizations; Hutu extremism; U.N. special rapporteur
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".