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Record W7051949401

The Politics of Multiculturalism and Nation Building: Managing Cultural Diversity in Malaysia.

2012· other· en· W7051949401 on OpenAlexfundno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2012
Typeother
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
FundersBritish Columbia Innovation Council
KeywordsLiquationArticular cartilage damageTubulopathyPretextCircumstantial evidenceDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.205
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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