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Record W7054348400

#AFringeMinority: Collective identity within the 2022 Freedom Convoy protests on social media

2024· article· en· W7054348400 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2024
Typearticle
Languageen
FieldChemistry
Topicthermodynamics and calorimetric analyses
Canadian institutionsnot available
Fundersnot available
KeywordsCollective identityCollective actionIdentity (music)Social movementSocial identity theorySocial mediaMediation
DOInot available

Abstract

fetched live from OpenAlex

In early 2022, Canada – and the world – was gripped by protestors’ disruptive occupation of Ottawa’s downtown core, and several Canada-U.S. border crossings. Operating under the banner of the “Freedom Convoy,” an amalgamation of far-right actors – from anti-government extremists, White nationalists, and anti- “vaxxers” – united against Canada’s COVID-19 public health mandates. Instructive to understanding the Freedom Convoy’s ascendance was their ability to construct a symbolically inclusive collective identity, and their use of social media to that end. However, there are three notable gaps hindering a fuller understanding of these processes: how far-right social movements use short-form video platforms, like the pandemic favourite, TikTok, to mediate their collective identity, and how protestors’ TikTok use for identity building compares cross-nationally, and across platforms. I aimed to remedy these gaps, making decisive contributions to our understanding of collective identity’s mediation on social media. First, I explore Canadian Freedom Convoy supporters’ use of TikTok for expressing collective identity frames. I uncovered that the movement’s anti-institutional collective identity was buoyed by TikTok users’ practices, including alternative broadcasting, monologuing, and audio memes. I argue that TikTok’s emphasis on visuality, personability, and imitability was beneficial to conveying the Freedom Convoy’s anti-institutional collective identity. Second, I investigated the Freedom Convoy cross-nationally, looking into Canadian and New Zealanders’ use of TikTok to communicate collective identity frames. I found that New Zealanders’ collective identity did not passively copy Canadians’ anti-institutional collective identity, but rather “re-contextualized” these frames within their own localized political struggles, national histories, and symbolic registers. Moreover, I found that New Zealanders’ TikTok practices subtly differed from their Canadian counterparts, working to better capture New Zealand’s socio-cultural specificities, and the forceful crackdown on protests in Wellington. Lastly, I examined Canadian Freedom Convoy supporters’ use of TikTok and Facebook to articulate collective identity frames. I found that, while certain practices transcended platforms’ borders (e.g., alternative broadcasting, monologuing), they were nevertheless mediated through platforms’ specificities. I also found evidence that other practices were more recalcitrant to being transmuted (e.g., audio memes, public relations messaging), owing to each platform’s material infrastructure, and culture of use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.313
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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