Elves, environmentalism, and “eco-terror”: Leaderless resistance and media coverage of the Earth Liberation Front
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past decade and a half, North America has seen a rash of environmentally motivated arsons. One group in particular, the clandestine Earth Liberation Front (ELF), has targeted ski resorts, genetic research labs, SUV dealerships, and forestry buildings, leading James Jarboe of the FBI to declare the ELF the “number one” domestic terrorist threat facing the USA. This article analyses the social construction of the “ecoterrorist threat” in the pages of the New York Times. Various stakeholders—including ELF spokespersons, moderate environmentalists, corporate interests, and state agencies—have sought to influence the way that media covers the ELF. Ultimately, much to the chagrin of ELF spokespersons, discourses of ecoterrorism have normalized in mainstream media, which regularly frames the spokespersons and activists as “dangerous clowns.” In turn, this coverage has prevented the expression of the ELF’s ideology, foreclosing the potential for the mainstream media to represent as legitimate the concerns of the ELF. I argue that blame for this failure rests in part with certain implications of the ELF’s organizational strategy of “leaderless resistance,” which—unlike civil disobedience movements of the past—is predicated on having its actors remain unsympathetically faceless and nameless.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it