Terrorism Made Simpler: A Framing Analysis of Three Canadian Newspapers, 2006-2013
Bibliographic record
Abstract
How do mainstream Canadian newspapers portray contemporary terrorism? The 9/11 terrorist attacks on the United States and the ensuing “war on terror” has deeply impacted media coverage of terrorism and terrorism-related events around the world. Canada is no exception and scholars have begun examining various aspects of terrorism coverage in the Canadian media system. Inspired by framing theory, the following study adds to this growing literature by developing a model for understanding and evaluating media coverage of terrorism according to “degrees of simplification.” The model is applied to a sample of articles drawn from three Canadian newspapers in two periods of time—June 2006-June 2007 and June 2012-June 2013. Three main findings are discussed. First, both The National Post and La Presse tended to present terrorism-related news and analysis using simpler frames than The Globe and Mail. Second, the coverage of domestic terrorism was far less simplistic than the coverage of international terrorism in all three newspapers. Third, while simplifying frames were more frequent in 2006-7 than in 2012-3, the study finds weak evidence that mainstream framing practices employed by the Canadian newspapers radically changed between these two time periods.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.032 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".