Harassment through Digital Media: A Cross-Jurisdictional Comparative Analysis on the Law on Cyberstalking
Bibliographic record
Abstract
The cyber world is an extension of the real world. It is another dimension where we can work, study and play. But people also tend to lose their inhibitions on the Internet, often while keeping their anonymity. Because of the perceived and real freedoms in the digital environment, people are emboldened to act in ways that they may not normally do in the real world. One recent phenomenon that is steadily becoming a problem in every country with a high level of electronic connectivity is the act of cyberstalking. The electronic medium is an important factor due to its very nature such as low cost and ease of use, potential anonymity and stealth as well as the insignificance of physical distance to the act of cyberstalking. Hence, cyberspace affords lesser impediments to aggressive behaviour. The borderless nature of electronic communications medium, concomitant jurisdictional concerns and the unique challenges posed to computer forensics such as the collection of evidence and investigations also arise as relevant issues in this context. Cyberstalking has become a concern that has translated into law in larger and more technologicallymatured jurisdictions such as the United States, the United Kingdom, Canada, Australia, Japan and even in a small country like Singapore. Existing laws relating to harassment or intimidation are often fact- or relationship- specific and are inadequate to meet the needs of modern society, while nascent cyberstalking laws are substantively disparate. I will first use Singapore as a case study and backdrop by presenting the factual experience and judicial developments in Singapore relating to cyberstalking and identify some of the usual problems in its treatment under law. I will then analyse and compare the cyberstalking laws of several key jurisdictions to determine the common elements and treatment amongst them with a view to the formulation of a proposed statutory solution that will take into consideration the different rights and interests of members of society in the use of digital media for social interaction. I will also briefly consider the issues of prescriptive, adjudicatory and enforcement jurisdiction and the need for greater international cooperation to deal with the problem through the harmonisation of substantive laws, the coordination in procedural investigative measures and complementary recognition and enforcement laws.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.014 | 0.018 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".