Positioning Muslims in Ethnic Relations, Ethnic Conflict and Peace Process in Sri Lanka
Bibliographic record
Abstract
Sri Lankan Muslims, the second largest minority ethnic group with 9.4 per cent (2012) of the total population has been victimized in the cause of ethnic politics, ethno-nationalism, and ethnic conflict in Sri Lanka. Like other ethnic groups in Sri Lanka, the Muslims also have a historical origin that follows a set of distinctive ethno-centric cultural and religious practices. They have contributed much to the communal harmony, socio-economic and political development of the country throughout the history of Sri Lanka. However, the ethnic distinctiveness of Sri Lankan Muslims has always been questioned and the community has been violently targeted in the cause of time. The ethnic politics and ethno-nationalism of both major ethnic groups, the Sinhalese and the Tamils have impacted a lot on the Muslims of Sri Lanka. Furthermore, most of the initiatives adopted to resolve the ethnic conflict have also failed to address the grievances and to accommodate the interests and demands of the Muslims. The devastating effects of the conflict on Muslim community and the continuous neglect of their interests in the discourses of peace process pushed them to politically mobilize for advocacy politics. On this backdrop, this paper pays attention on the historical survival of Muslim community, their position in ethnic politics and peace process in Sri Lanka. The main objective of this paper is to record the historical incidents related with the Muslims in Sri Lanka without pointing fingers at any party in these processes. The analysis of this paper is descriptive and interpretive in nature and only the secondary data is used for the analysis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".