The kids are not alright: Children as objects, audience, and agents in the 2022 Canadian convoy protests
Bibliographic record
Abstract
Abstract Children figure prominently in far‐right movements, ideologies, and conspiracy theories as innocent targets of nefarious and decadent forces, unwitting symbols of social and political decay, and potentially dangerous objects of moral panic. Far‐right movements thus map a wide‐ranging network of concerns about immigration, race, public health, education, and globalization onto children's bodies and spaces. Yet children and youth also actively participate in these movements or are otherwise socialized into them, inhabiting and making the everyday geographies of the far right in numerous ways. Children's presence at and participation in a series of protests and occupations in Canada in early 2022 demonstrates well their place in far‐right movements as symbols and agents, and connects the Canadian far right to broader spatial and temporal perspectives shared across the transnational landscape of such movements. These protests, dubbed the “Freedom Convoy” by participants and ostensibly aiming to end vaccine mandates in the Canadian trucking industry, quickly turned to more general antigovernment demands and became far‐right networking events. This paper examines more closely children's presence at and participation in the Canadian protests and how the movements behind them position children as object, audience, and agent in the spatiality of the far right's current transnational resurgence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".