Tie a Yellow Ribbon ‘Round Public Discourse, National Identity and the War: Neoliberal Militarization and the Yellow Ribbon Campaign in Canada
Bibliographic record
Abstract
The yellow ribbons that have become so ubiquitous in Canada as the emblem of the national Support Our Troops campaign are highly charged semiotic tools in a battle for control of public discourse, marking the growing militarization of Canadian society in an age of empire. I read the Yellow Ribbon here as neoliberal cultural pedagogy, an everyday means by which individuals learn and teach specific cultural values and tropes, both explicitly and implicitly. As a symbol and a commodity, and perhaps more importantly as an everyday social and cultural practice, the Yellow Ribbon offers a glimpse into the dense cultural and political forces involved in the re-scripting of Canadian national mythologies,according to a logic of militarized neoliberalism.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.044 | 0.034 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".