The Reshaping of Landscapes: Systems of Mediation, War, and Slow Violence
Bibliographic record
Abstract
John Lee's, David Fedman's, and Lisa Brady's essays persuasively show the value of studying environmental issues on the Korean peninsula. Each of the essays carefully explains how drives led by individuals and entities, such as the state, engineered nature for human needs, security, and later economic growth. In so doing, they show how these drives simultaneously altered nature and remade institutions, systems, and cultures that influenced people's agency and identity and reshaped forms of consciousness. By judiciously making visible the agents and social forces behind the reconstitution of nature, the essays collectively introduce diverse approaches to the study of environmental issues in Asia and elsewhere. Most of all, they demonstrate that transnational environmental history on the Korean peninsula can no longer be overlooked when dwelling on and debating major historical and theoretical issues in Korean, Asian, and environmental studies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.049 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".