The Use of TikTok for Political Campaigning in Canada: The Case of Jagmeet Singh
Bibliographic record
Abstract
TikTok is a critical platform for political campaigns seeking to engage with new publics through digital advocacy. Jagmeet Singh, the leader of Canada’s New Democratic Party, has emerged as a TikTok celebrity since establishing his profile in 2019. At the time of writing, he is the only Canadian federal party leader using TikTok with his interactions greatly surpassing those on his other social media profiles. Strategically utilizing TikTok to promote his social justice-oriented political platform and to build momentum in preparation for a snap election, his digital campaign has received extensive attention from the Canadian press. Through qualitative content analysis of his videos and news media coverage of Singh’s activity on TikTok, this article questions how his TikTok profile thematically engages with social democratic politics within the context of the permanent campaign. Attention is directed toward how Singh employs TikTok’s features to establish his brand of left-wing populism and advocate against systematic social inequality to appeal to TikTok’s youthful demographic.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.069 | 0.014 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".