Strengthening Intelligence Surveillance as a Counterterrorism Measure in Indonesia and Canada
Bibliographic record
Abstract
This paper examines some of the legal issues that occur in Indonesia and Canada related to the use of surveillance technology to fight against terrorism. It also explores a few of the issues raised with respect to the protection of the right to privacy as a fundamental right in both countries, especially in the context of gathering information through surveillance technology. This study finds that both Indonesia and Canada do not explicitly state the right to privacy in their constitutions. One difference between the two countries in terms of their approach to using surveillance technology in combating terrorism is that Indonesia places a significant emphasis on national security, which can result in a partial sacrifice of the right to privacy for suspected individuals. Conversely, Canada has a legal framework for surveillance and interception, supported by a well-established legal jurisprudence that addresses the specific legal requirements applicable to surveillance methods in various situations. Indonesia’s legal framework regarding surveillance lacks clear limitations on when surveillance becomes excessive and violates the right to privacy. In Canada, the general requirement to obtain a search warrant from a court serves as a safeguard to protect against potential infringements of fundamental rights, although it does not guarantee flawless protection in all circumstances. Breaches can still occur and be challenged in court.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".