Twitter, YouTube, and Flickr as platforms of alternative journalism: The social media account of the 2010 Toronto G20 protests
Bibliographic record
Abstract
This article examines the appropriation of social media as platforms of alternative journalism by the protestors of the 2010 G20 summit in Toronto, Canada. The Toronto Community Mobilization Network, the network that coordinated the protests, urged participants to broadcast news using Twitter, YouTube, and Flickr. This particular use of social media is studied in the light of the history and theory of alternative journalism. Analyzing a set of 11,556 tweets, 222 videos, and 3,338 photos, the article assesses user participation in social media protest reporting, as well as the resulting protest accounts. The findings suggest that social media did not facilitate the crowd-sourcing of alternative reporting, except to some extent for Twitter. As with many previous alternative journalistic efforts, reporting was dominated by a relatively small number of users. In turn, the resulting account itself had a strong event-oriented focus, mirroring often-criticized mainstream protest reporting practices.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".