Bibliographic record
Abstract
When and where did the environmental movement begin? Stepping back from the limitations of national history, this book examines the question of environmental origins on a global scale. In the late nineteenth and early twentieth century the most sweeping environmental initiatives emerged under the auspices of British imperialism. As the following study will show, hard-headed environmentalists and legislators found in empire forestry a ready-made model to persuade the public that the reservation of vast areas of the public domain would serve settlers, industrial development, governmental revenue, and environmental purposes. Empire forestry resolved the tension between romantic preservationist notions and laissez-faire policies. This book traces the international trail of environmentalism from India, under Lord Dalhousie's Forest Charter, to the British colonies in Africa and Australasia where it matured and, finally, to Canada, the United States, and other parts of the globe where environmentalism permanently entered the pantheon of political creeds. By the First World War a large area of forested land around the globe lay in the public trust, managed by a professional cadre of government foresters. In the British colonies alone the crown had environmentally protected a land mass equal to ten times the size of Great Britain. Concurrently in the United States, after transferring 1 billion acres of public land into private hands in the early and mid 1800s (approximately one-half of the land mass of the continental United States) a change suddenly occurred.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.519 | 0.359 |
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".