Four arenas: Malaysia’s 2018 election, reform, and democratization
Bibliographic record
Abstract
Malaysia’s 2018 election ended more than six decades of dominant party rule by the United Malays National Organisation (UMNO). Three questions are paramount. How did the opposition finally achieve victory? What did voters who rejected UMNO actually vote for? Finally, what do the answers imply for reform and democratization? We argue that Malaysia is comprised of four distinct identity-based polities, each with a unique electoral dynamic and vision for the country’s political future. Using this framework provides valuable insights into UMNO’s defeat, which was achieved by making inroads, largely through elite splits, into two arenas that were previously impenetrable for the opposition. One arena remains electorally pivotal and thus exerts a disproportionately large influence on the new government’s reform agenda, entrenching the primacy of identity politics and ensuring the continuity of many policies that address ethnic relations. The case illustrates the extensive impact of divided polities and regionalism on democratization.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".