The Social Study of Information Work: StopFake.org and Ukraine's Online War with Russia
Bibliographic record
Abstract
The grassroots Ukrainian organization, StopFake.org,performs the information work of combatting Russiangenerateddisinformation. The Internet allows anetwork of supporters scattered around the world toevaluate, and undercut, claims made in Russianpropaganda. This case illustrates that virtual internetcommunities can distribute work that once required acentralized, well-financed team.L’organisation populaire ukrainienne, StopFake.org,effectue le travail informationnel de lutter contre ladésinformation générée par la Russie. L’Internetpermet à un réseau de sympathisants éparpillés depar le monde d’évaluer et d’atténuer les allégationsformulées par la propagande russe. Ce cas illustre lefait que des communautés virtuelles reliées parInternet peuvent distribuer le travail qui nécessitaitautrefois une équipe centralisée et bien financée.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.017 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".