Ad Baculum, Islamic State and Malaysian Chinese Politics: A Rhetorical Study of Selected Political Advertisements in the Local Chinese Media during the 11th Malaysian General Election Campaign
Bibliographic record
Abstract
This study analyzes the rhetorical strategy of using the emotion of fear as a political tool in the 11th Malaysia General Election campaign. The three-prong objectives of this study are to analyze the main themes and issues used to address this tactic of fear, the general perceptions that non-Moslems in Malaysia have of the concept of Islamic state as a symbol of fear and rhetorical strategies used to provoke this fear. The scope of the study is confined to the conventional communication model of “Source-Message-Channel-Receiver”. The “sources” are political advertisements, the “messages” are Islamic state theme and related issues, the “channels” are symbols or rhetorical strategies and the “receivers” are the voters, with special reference to Malaysian Chinese voters. The findings concluded that the National Front party (Barisan National, BN) used the fear factor effectively in its campaign. This situation is further enhanced by the strong control of BN over the Malaysian media in addition to the character of Chinese voters who generally prefer not to leave their current comfort zone and are afraid of an Islamic state.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".