The Politics of Multiculturalism and Nation Building: Managing Cultural Diversity in Malaysia.
Bibliographic record
Abstract
The issues and challenges facing multicultural societies around the globe could plausibly be argued to be similar in nature. The demand for recognition by certain segments or compartments in society calls for further examination of these demands and how the demands fit with the politics adopted by the respective states. However, the social, political and economic landscape of each particular society has a bearing on the policies formulated to address these issues and challenges. This has given rise to terms such as plural society, multicultural society, multi-ethnic and multi-religious societies to indicate the existence of such variants in a society. As for Malaysia, its colonial experience can be identified as one of the factors that contributed to the formation of a multicultural society and later to the formulation of policies which sustained the formation of a multicultural identity. Nevertheless, the main issue and challenge facing multicultural Malaysia is to grapple with the idea of national integration. Does this indicate that by recognising multiculturalism means that one has to face the issue and challenges of national integration? It is here that one would normally argue for an assimilationist approach to be adopted in order to ensure national integration. It is my hope that this dissertation is able to highlight the issues and challenges facing multicultural Malaysia and to make some contribution to addressing the issues and challenges faced.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".