Bibliographic record
Abstract
Canada's response to terrorism has been dramatically affected by 9/11. Canadians died in the horrific attacks on the World Trade Center, but so did the citizens of many other countries. What was unique about Canada's response to 9/11 was the border it shares with the United States. The border meant that Canada felt the repercussions of the swift American response to the attacks in an immediate and profound manner. For example, when the United States closed its air space that terrible day, it was Canada that accepted over 200 airplanes destined for the United States, including one plane that was erroneously believed to have been hijacked. Canada also was affected by erroneous claims that some of the terrorists had entered the United States through Canada, as indeed had occurred before and may likely occur again given the millions who cross the border each day. Canada was also singled out in the USA Patriot Act which contained a whole section entitled ‘Defending the Northern Border’ providing for increased border guards and scrutiny of those entering the United States. Important components of Canada's anti-terrorism and immigration policies have been established in border agreements with the United States. Canada has drafted broad new anti-terrorism laws and developed a new public safety department of government with an eye to American perceptions that Canada might provide a safe haven for terrorists.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".