Revisiting the Double Actionability Rule in Singapore: Time for a Change
Bibliographic record
Abstract
The double actionability rule, which was first laid down in the 19th century, has been the subject of considerable academic and judicial criticism. Over the years, several jurisdictions around the world have abandoned the double actionability rule in favour of alternative choice of law rules for torts. Canada, in two landmark decisions, reconsidered its earlier jurisprudence on the applicable choice of law rules for torts, as well as multijurisdictional defamation cases in particular. However, the apex court in Singapore has unquestioningly adopted the double actionability rule as part of Singapore law in a series of cases starting in the 1990s. Unfortunately, the seeds of reform that were sown by the lower courts at various points in time have been largely ignored. This article argues that in the light of recent developments and changing circumstances, the time is now ripe for Singapore to follow the lead of Canada and many other jurisdictions in departing from the double actionability rule.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".