<i>AHR</i>Conversation: Environmental Historians and Environmental Crisis
Bibliographic record
Abstract
Environmental history is no longer new. Neither, of course, is the notion of environmental crisis. But they are bound together. It might be said, in fact, that historians' interest in the environment as a legitimate and urgent subject for historical study only crystallized as a field when the deteriorating state of the environment became an issue of public concern in the 1970s. Thus, if environmental historians are not solely interested in dramatic and often cataclysmic change, they surely have been alert to the ways in which human history has been marked, often disastrously, by profound alterations in our natural world. The topic of this year's AHR Conversation is “Environmental Historians and Environmental Crisis.” We were obviously moved to choose this topic by present-day concerns with the environment, but the discussion itself provides a historical perspective on the problem, something that is usually missing from contemporary discussion. It also stresses the methodological issues and challenges of doing environmental history, providing, we hope, readers with a snapshot of the field in its present state. The five participants represent a global and chronological mix of perspectives. Richard C. Hoffmann is an early modern and medieval historian at York University, Toronto; Nancy Langston is a U.S. historian at the University of Wisconsin–Madison; James C. McCann is an African historian at Boston University; Peter C. Perdue is a specialist in China at Yale University; and Lise Sedrez is a Latin American historian at California State University, Long Beach. The Conversation was moderated by the AHR Editor.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".