Bibliographic record
Abstract
Communications surveillance in Korea is alarming. Per capita, acquisition of subscriber identity data is 60 times, wiretapping 9.5 times, pen register/trap and trace data 2 times, cell tower dumps 5 times the U.S., even taking into account NSA and Foreign Intelligence Surveillance Court procedures put into controversy by the recent Snowden revelations. Specific instances of surveillance are noteworthy: seizure of 7 years worth of electronic mails for a campaign financing investigation into a local school board supervisor election, which lasted for 3 weeks; renewing a wiretapping order 14 times over several years. Especially, cell tower dumps involve astronomic amounts of communication metadata, and their constitutionality under the warrant doctrine must be closely examined for they constitute a search on a specific individual with reasonable suspicions but a search for such person. The decisions from U.S. lower courts denying or restricting the conditions of cell tower searches are informative in that regard, and so should the international human rights statements evaluating the mass surveillance conducted by NSA and FISC in the similar spirit of a search for a suspect. Also, warrantless acquisition of subscriber identification data, while violating the warrant doctrine itself, also greatly facilitate, and thereby incentivizes the investigatory authorities into, mass surveillance by allowing the authorities to check the identities of otherwise anonymous callers en masse. The April 2014, Spencer decision from the Canadian Supreme Court striking down a law allowing such warrantless access should be consulted, and also the Marco Civil of Brazil passed in March of the same year also established that the identification data must be accessed only through a court order.Another reason for massive expansion of communication surveillance in Korea is the lack of timely notification to the suveilled. For instance, the notifications of wiretapping, metadata acquisition, and electronic search and seizure are allo given not on the N-th day after execution but on the N-th day after the investigation is completed and the indictment/no indictment decision issued, which means often the surveilled find out about the fact of surveillance for the first time in court when the prosecutors present the incriminating transcripts in evidence. Subscriber identification data, being warrantlessly accessed, are also accessed without notifications to the subscribers. Also, the recent telecoms’ refusal to let their users in on whether the subscriber identification has been done on them is also violative of the subscribers’ rights as the consumers. The lack of notifications insulates judges from feeling the real pervasiveness of surveillance and hampers their efforts to balance privacy and public interest properly, allowing the surveillance disproportionate in quality and quantity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".