CATALOGING PROTEST: NEWSPAPERS, NEXIS UNI, OR TWITTER?*
Bibliographic record
Abstract
What is the best source for tracking protest activity? Newspaper sources remain dominant, but other options are tempting. This article compares three differently sourced catalogs of protest events in Toronto from July 15 to September 15, 2020. The widely discussed Movement for Black Lives and housing justice cycles of protest are visible in all three catalogs, but apart from this, the field of protest they reveal is very different. While the coverage by the newspaper with the largest circulation, the Toronto Star, shows Toronto protest as state-centered, domestic, and progressive, other catalogs that include television, radio, and social media content reveal a more diverse, fragmented, and globalized protest field. Catalogs sourced from Nexis Uni and Twitter show the significant presence of diasporic protest. These observations suggest new limits to relying on mainstream newspapers for representing the full array of protest activity. We recommend that, moving forward, researchers experiment with media aggregators to incorporate sources such as television coverage and social media into their research while remaining aware of the additional challenges such data generate.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".