Human Rights in the Global Village: The Challenges of Privacy and National Security
Bibliographic record
Abstract
We live in a global village within which international and domestic human rights intersect and both fall under the cloud of terrorism and concerns about national security. The author argues that our basic human rights should not be sacrificed on the altar of national security but rather basic rights, such as privacy, should be carefully balanced against the collective need for security.\nWhile claims can be made for a constitutional right to privacy, it is largely a statutory concept that can fall victim to other political imperatives such as fighting terrorism. Privacy is a casualty of the war on terror but racial profiling and restrictions on liberty are other problems that emerge from a broad definition of terrorism and an expansion of executive discretion. Information flow, the vital and non-neutral role of technology, and the growing sense of the state's right to know poses serious threats to the privacy of the individual in the post 9/11 world. While the Canadian response to terrorism has been more moderate than in the United Kingdom and the United States, there are still serious threats to privacy and other basic right in Canada; as evidenced by Security Certificates, secrecy laws and the export of technology to repressive regimes, such as China.\nThe author ends on a call for attacking the root of causes of terrorism such as poverty and economic disparity in the world. He also suggests that democracy, respect for basic human rights and the rule of law are the true allies in the quest for national security, and not its enemies. Terrorism poses a real threat to the Global Village but the best answers can be found in the classic Canadian values of moderation and balance.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.042 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".