Divided into Stands, Together they Fall: A critical analysis of salvage logging in the Rogue-Siskiyou National Forest
Bibliographic record
Abstract
This research takes elements of the scholarship on environmentalism -- political theory and ethical philosophy -- and evaluates them together in the context of the conflict over salvage logging in the Rogue-Siskiyou National Forest in Oregon. I tell the story of the conflict through a history of land and fire management in the U.S. Through a closely detailed account of the anti-salvage logging activism, I explore the gap between ethics and political responsibility and how they unfold in this battle against deforestation. This research offers an in-depth look into how the environmental movement struggled internally to identify goals, and to challenge powerful economic and political systems that prevent significant change from taking root. I argue that the environmental movement needs a theory of environmental responsibility as a framework by which to better understand the strategies and complexities of environmental conflicts. The task of environmental responsibility is to confront the challenge of how to make the environmental movement responsive to the political and economic conditions that produce conflicts, and how environmentalism can overcome the limits of liberal individualism. As forests continue to dwindle, and as activists across the nation mobilize to stop the Keystone XL pipeline that will carry Canadian tar sands to the Gulf of Mexico, the future of environmentalism has never been more critical.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.024 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".