RACIAL AND RELIGIOUS HATE SPEECH IN SINGAPORE: RECLAIMING THE VICTIM’S PERSPECTIVE
Bibliographic record
Abstract
In this essay, I argue that the rationales offered by the Singapore Government for restricting racial and religious hate speech are not only constitutionally unsound, but also not without serious moral and social costs. I start off identifying two main rationales offered for the existing restrictions, namely (1) the maintenance of public order, and (2) the promotion of an ethic of intercultural tolerance. These twin rationales are buttressed by a literalist (and flawed) judicial interpretation of the right of free speech under Article 14 of the Singapore Constitution. Drawing on hate speech decisions from the U.S., Canada and Europe, I advance a more faithful reading of Article 14 which affords greater constitutional protection for hate speech as 'political speech'. I next trace how the Singapore Government's regulation of hate speech is rooted in its avowedly Asian-style 'communitarianism'. The 'public order' and 'tolerance' rationales, however, fail to recognize that race and religion are constitutive aspects of our individual flourishing and self-respect, which hate speech attacks. The present legislative regime is therefore guilty of self-contradiction. Lastly, I sketch a different, victim-centred justification for Singapore's hate speech laws which is responsive to the profound injury inflicted upon individuals targeted by racial and religious vilification. This victim-centred perspective, it is suggested, finds a comfortable textual home in Article 152(1) of the Singapore Constitution, which requires the Government to care for the interests of racial and religious minorities in Singapore.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".