Crimes Against Humanity The Case of the Rohingya People in Burma
Bibliographic record
Abstract
Burma’s Rohingya Muslims are currently subject to crimes against humanity by the Burmese government, witnessed in recent acts of murder, torture, forced displacement, imprisonment, religious persecution, and restriction of movement. Should the Burmese state fail to end such crimes against humanity, there is potential for the situation to escalate to genocide. Given its mandate “to ensure that the government of Canada does all that it can to prevent and protect civilian populations from genocide and crimes against humanity, ” the All‐Party Parliamentary Group for the Prevention of Genocide and Other Crimes Against Humanity is urged to take immediate action. i Notably, Canada should be encouraged to use regional diplomatic relations to lobby for amendments to Burma’s 1982 Citizenship Law, strengthen diplomatic relations with Burma and establish and host a truth commission to overcome recent violence. Burma’s (Myanmar) Demographics Burma’s 1 dominant ethnic group is the Burmese, accounting for 68 % of the country’s population of 55,167,330. ii A number of minority ethnic groups are also present, representing small portions of the population: Shan (9%), Karen (7%), Rakhine (4%), Chinese (3%), Indian (2%), Mon (2%) and other (5%). iii Buddhism is the predominant religion in Burma, accounting for 89 % of the population. Christians and Muslims represent ~4 % of the population, respectively. iv While Buddhism is not the state religion, the majority of the Burmese tend to follow the Theravada school of Buddhism. v Reports indicate that the
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.021 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".