Securitization Theory and the Relationship between Discourse and Context: A Study of Securitized Migration in the Canadian Press, 1998-2015
Bibliographic record
Abstract
This article addresses the problem of the significance of empirical variation in security moves towards immigration and the consequent question of the role of context in securitization theory. Drawing on the analysis of a set of 4,464 newspaper articles published by La Presse and the National Post on the subject of international immigration to Canada between January 1, 1998, and December 31, 2015, it investigates the link between the frequency with which these two Canadian broadsheet dailies depict immigration as a threat to the physical well-being of the state or its population and the occurrence of six major migratory events. It finds that the saliency of security discourse on immigration in the written press is strongly and positively impacted by the incidence of such events. The paper also proposes further conceptualization of the cohabitation and complementarity between exceptional and routinized securitization practices.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".