E-Bandits in Global Activism: WikiLeaks, Anonymous, and the Politics of No One
Bibliographic record
Abstract
In recent years, WikiLeaks and Anonymous have made headlines distributing confidential information, defacing websites, and generating protest around political issues. Although many have dismissed these actors as terrorists, criminals, and troublemakers, we argue that such actors are emblematic of a new kind of political actor: extraordinary bandits (e-bandits) that engage in the politics of no one via anonymizing Internet technologies. Building on Hobsbawm's idea of the social bandit, we show how these actors fundamentally change the terms of global activism. First, as political actors, e-bandits are akin to Robin Hood, resisting the powers that be who threaten the desire to keep the Internet free, not through lobbying legislators, but by “taking” what has been deemed off limits. Second, e-banditry forces us to think about how technology changes “ordinary” transnational activism. Iconic images of street protests and massive marches often underlie the way we as scholars think about social movements and citizen action; they are ordinary ways we expect non-state actors to behave when they demand political change. E-bandits force us to understand political protest as virtual missives and actions, activity that leaves no physical traces but that has real-world consequences, as when home phone numbers and addresses of public officials are released. Finally, e-banditry is relatively open in terms of who participates, which contributes to the growing sense that activism has outgrown organizations as the way by which individuals connect. We illustrate our theory with the actions of two e-bandits, Anonymous and WikiLeaks.
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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 | 0.002 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".