The justification of anti-terrorism legislation in Australia and Canada between September 17, 2001 and March 31, 2003
Bibliographic record
Abstract
Few countries had seen the necessity for anti-terrorism legislation prior to 11 September 2001 (9/11) but that worldwide shock resulted in the United Nations Security Council Resolution 1373 calling for measures to combat international terrorism on 28 September 2001. Australia and Canada, middle powers at the United Nations, and close allies with the United States, were among the first to react in support of counter-terrorism action, Australia invoking the ANZUS Security Treaty between Australia, New Zealand, and the United States of America, and Canada supporting the response to 9/11 through the North Atlantic Treaty Organization. Both countries were quick to begin drafting anti-terrorism legislation that would fulfil the United Nations requirements under Resolution 1373 targeting the financing of terrorism and other actions. Canada introduced its anti-terrorism legislation on 15 October 2001 and Australia, having had an election in November 2001, began debating its anti-terrorism legislation on 13 February 2002. <br><br>This dissertation investigates the legislative discourse on anti-terrorism laws as the elected Members of Parliament in Australia and Canada debated the proposed new measures between 17 September 2001 and 31 March 2003, the period covering the passage of most of the early anti-terrorism legislation. The research aims to determine how the new laws, necessary at the time because of an increased awareness of the international character of terrorism, would be justified considering the increased law enforcement powers proposed in parts of the new legislation. There was a perceived lack of capacity to deal with terrorism in existing criminal laws. Terrorist acts were identifiable as crimes but were regarded differently and prevention was one aspect of this difference. Terrorism seemed to call for differentiation in the law but a major difficulty was in clarifying inherent characteristics of terrorism. <br><br>The verbatim records of parliamentary debates in both countries, documented in Hansard, provided an authoritative source of the views expressed by politicians, on the government side introducing and supporting the reasoning for the new legislation, and on the opposition side by the several political factions represented, each with a party policy and purpose to uphold. Forty-five themes were identified as topics through which anti-terrorism legislation was debated. Every time a Member of Parliament spoke on a topic related to a theme, an instance was recorded, creating a database of over 5,000 instances. The four key topics forming the basis for the new legislation were the Terrorism Event, National Security, Criminal Justice and Anti-Terrorism Legislation. Statistical comparison of the discourse quantities produced in relation to each theme did not support the hypothesis that the introduction of Anti-Terrorism legislation was discussed predominantly as a national security issue in Australia and a criminal justice issue in Canada.<br>
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".