MGR Quarterly Infographics Report: July - September 21, 2023
Bibliographic record
Abstract
MGR recorded 4466 violent incidents from July to September 2023, mostly triggered by politics, access to resources, and other socio-economic factors. More than 744 deaths and 5249 injuries have been recorded from these incidents. The highest number of violent incidents have been recorded in the form of clashes and attacks (1110). Some 1043 incidents are directly or indirectly political violence which resulted in 52 deaths. Geographically, Dhaka (909) scores the highest number of violence followed by Chittagong (904), Rajshahi (668), and Khulna (700). There were 582 protests and demonstrations and at least 413 were triggered by politics. While some 27.62% of political violence contributed by Bangladesh Awami League & affiliates, 15.31% contributed by the Bangladesh Nationalist Party (BNP). Intra-party violence within the Awami League maintains a significant surge in the third quarter of 2023. Whereas 63% incidents were rural, 37% violence incidents took place in urban areas in this quarter. During the third quarter, Bangladesh experienced a significant increase in incidents of student violence, with a total of 226 cases reported across different regions. A notable finding was that approximately 38% of political violence were directly linked to student or campus-related conflicts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".