Bibliographic record
Abstract
While much has been said about the global war on terror, the concept remains cunningly elusive and yet undeniably pervasive. This collection of essays is an effort to discover the Canadian "self" through exploration of the terrorist "other." Understanding Terror:Perspectives for Canadians as a collection, views the war on terror from unique eyes. It defines the boundaries of terror, examines its construction in the media, and explores its relationship to the Muslim "other." Understanding Terror: Perspectives for Canadians takes a historical approach to consideration of terror through specific examples and its presence in the media, in North American society, and particularly in Canada. Contributors to the volume include journalists, scholars, and public policy experts, many of whom have viewed or experienced terror first-hand. Their aim is to examine specific events, reflect on how those events might be interpreted, and provide historical context, all the while encouraging the reader to question preconceived characterizations of this highly charged political and cultural issue. The book includes essays by Gwynne Dyer, Major Brent Beardsley, Stuart Farson, Doug Firby, Ronald Glasberg, James P. Lassoie, George Melnyk, and Reg Whitaker.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".