Analyzing the Freedom Convoy through demand and supply-side perspectives in far right literature
Bibliographic record
Abstract
This thesis explores the Freedom Convoy (FC) movement by connecting it to the extensive literature on the recent far-right phenomenon, including extreme, radical, and populist variants. The FC (January 22nd to February 23rd, 2022) involved a number of Canada-wide protests targeting large cities, smaller communities, border-crossing points with the United States (US), and most importantly, the city of Ottawa, where the protest turned into a nearly month-long occupation. The FC, which differs from typical party-based far-right examples, serves as a unique case of far-right mobilization. Although the FC’s connection to the far-right movement has been established through mutual activists and organizations, no comprehensive analysis has previously connected far-right research to the FC. This study will address this gap using far-right literature. Although Eurocentric and party-centered, far-right literature provides valuable insights into protest-based and non-Eurocentric far-right movements, such as the FC. The methodology of this study will thus involve a thematic review of far-right literature, highlighting the importance of studying non-European and protest-based movements within the context of far-right literature. Additionally, this study examines how the FC was shaped by the COVID-19 pandemic and social media.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".