Res Ipsa Loquitur: Some Recent Cases in Singapore and its Future
Bibliographic record
Abstract
Res ipsa loquitur applies when a plaintiff who is injured in an accident does not know the precise cause of the accident and has to rely on the occurrence of the accident itself, as an event which does not happen in the ordinary course of things without the negligence, to infer negligence on the part of the defendant. The plaintiff in such a situation is relying on circumstantial or indirect evidence to raise a prima facie case of negligence against the defendant. Used in this way, res ipsa loquitur is an ordinary rule of evidence and it is not peculiar to the tort of negligence. Recent cases in Singapore have adopted this view of the effect of res ipsa loquitur and a Supreme Court of Canada decision has recently held that the Latin phrase employed in this way is useless and confusing, and should be abandoned in the tort of negligence. However, res ipsa loquitur has been used in some older English cases as something beyond a general rule of evidence. It is a unique and a substantive rule of law that shifts the legal burden of proof from the plaintiff to the defendant. On this application of res ipsa loquitur, the plaintiff raises a prima facie case of negligence against the defendant from which a court must, at the conclusion of the case, infer negligence, unless the defendant gives a reasonable explanation to disprove the presumption of negligence against him. The defendant is prevented by this use of the doctrine as a special rule of law from exploiting his exclusive and advantageous knowledge of the exact cause of an accident to the detriment of a plaintiff. The issue that is confronted in this article is whether res ipsa loquitur should perish in Singapore as something that merely signifies an ordinary rule of evidence or survive as a unique rule of law in the tort of negligence to correct the imbalance of knowledge that arises in the appropriate cases of proof of negligence by circumstantial evidence.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".