In search of a privacy action against breaches of physical privacy in Hong Kong
Bibliographic record
Abstract
The focus of privacy laws in Hong Kong has always been on the use and dissemination of personal or confidential information, but a person’s privacy can also be intruded by unwanted watching or listening irrespective of whether information is collected or used. Despite an attempt to introduce two privacy torts by the Law Reform Commission of Hong Kong in 2004, there is no timetable as to when these two statutory torts be introduced. Recognition has been afforded for intrusions upon seclusion or solitude in a number of jurisdictions including New Zealand and the Canadian province of Ontario. In England, an intrusion tort has not been separately recognized, but the decision in Gulati v MGN confirmed that damages may still be awarded for an action for misuse of private information in instances where there is no disclosure or publication of the wrongfully acquired information. This article looks at the possibility of developing a common law action of privacy in Hong Kong which affords protection regardless of whether private information is acquired or published by drawing insights to the developments in New Zealand and England.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".