Infiltration and Efficacy: A Performance Analysis of Ecoactivism in the Age of Corporate Hegemony
Bibliographic record
Abstract
In 1971, the group that would eventually become Greenpeace attempted to sail from Vancouver to Amchitka Island—twice—to witness and protest the American nuclear testing taking place on the island. The global media attention that the effort garnered motivated the United States to end the testing and restore the island to a bird sanctuary (Durland 67–68). Since that time, Greenpeace has become one of the largest and most influential environmental nongovernmental organizations in the world with offices covering operations in “more than 55 countries” and a purported 2.5 million individual donors (Greenpeace, “Who We Are”). The group relies heavily on direct action in its work against nuclear proliferation, whaling, toxic waste mismanagement, single-use plastics, and a host of other environmental issues; these actions are often so dramatic that Greenpeace has been theorized as a guerrilla theater company (Durland 68). In 2015, Greenpeace launched the Detox Outdoor campaign in an effort to eliminate the use of perflourinated and polyflourinated compounds (PFCs) from the supply chain of major outdoor brands like The North Face, Columbia, and Patagonia. PFCs are chemicals that are often used in waterproofing for outdoor products like jackets, gloves, and sleeping bags: they have been shown to accumulate inside the body of living organisms, been detected in the bloodstream of humans, and are linked to reproductive disorders (Cobbing et al. 2). In this multifaceted campaign, the group relied heavily on performance-based actions, including an online meme action in which activists posed nude in extreme environments and held banners with messaging directed at the companies, storefront occupations in which activists placed themselves in front of and in the display windows of retailers wearing nothing but boxes printed with messaging criticizing the companies’ behavior, and two separate performance hikes that illustrated (1) the presence of PFCs in the environment and (2) the possibility of a world without them, respectively. In 2017, Greenpeace declared victory when Gore Fabrics—a major supplier for all of these outdoor brands—committed to eliminating hazardous PFCs from every part of their supply chain by 2023 (Greenpeace, “You Did It!”). In this campaign, it seems, performance worked—it did something.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.043 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".