Bibliographic record
Abstract
This paper discusses the Cham communities in Ninh Thuan Province, Vietnam. The Cham people are one of 54 state recognized ethnic groups living in Vietnam. Their current population is approximately 130,000. They speak a language which belongs to the Malayo-Polynesian language family. In the past, they had a country called, Champa, along the central coast of Vietnam, which was once prosperous through its involvement in maritime trade. While the largest concentration of the Cham people in Vietnam is found in a part of the former territory of Champa, particularly Ninh Thuan and Binh Thuan provinces, there is another group of Cham people living in the Mekong Delta, mostly in An Giang province near the border with Cambodia. There are differences in ethnic self-identification between these two groups of Chams living in the different localities. In general, the Chams living in the former territory of Champa equate being Cham as being descendants of Champa while the Chams of the Mekong Delta view being Cham as being Muslim. This paper is an attempt to understand the ethnicity of the Cham communities in Ninh Thuan Province through their religious system, particularly a dual structural principle in Cham cosmology called Awar and Ahier. In this paper, I argue that the concepts of Ahier and Awar, hold the key to understanding the way their ethnicity has been constructed and reveals an interesting aspect of their world view. In the course of the discussion, their indigenized form of Islam called Bani religion, which is peculiar to the Cham community will be introduced.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".