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Record W2140388994 · doi:10.1086/ahr.113.5.1431

<i>AHR</i>Conversation: Environmental Historians and Environmental Crisis

2008· article· en· W2140388994 on OpenAlexaboutno aff
Richard C. Hoffmann, Nancy Langston, James C. McCann, Peter C. Perdue, Lise Sedrez

Bibliographic record

VenueThe American Historical Review · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsConversationEnvironmental crisisSubject (documents)Environmental historyEnvironmental ethicsHistoryNatural (archaeology)State (computer science)Political scienceEnvironmental changePolitical economySociologyEconomic historyArchaeologyPhilosophyClimate changeEcologyBiology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.008
Scholarly communication0.0130.011
Open science0.0020.008
Research integrity0.0110.021
Insufficient payload (model declined to judge)0.0150.003

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.

Opus teacher head0.011
GPT teacher head0.194
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2008
Admission routes1
Has abstractyes

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