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Record W7067703441

Nature's Past Episode 051: Has Environmental History Lost Its Way?

2016· other· en· W7067703441 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2016
Typeother
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental historyScholarshipPower (physics)PoliticsEnvironmental movementEnvironmentalismSocial history (medicine)Materialism
DOInot available

Abstract

fetched live from OpenAlex

Late last year in December, Lisa Brady, the editor of the journal, Environmental History, posted a provocatively titled blog article, “Has Environmental History Lost Its Way?” In that article, she reviews a round table panel from the most recent annual meeting of the Organization of American Historians in which Mark Hersey, a historian from Mississippi State University challenged the audience to consider whether or not environmental history has broadened too widely in its scope and drifted from its methodological roots. \n \nTwo years earlier, Liza Piper, a Canadian environmental historian from University of Alberta, wrote a similarly provocative article in History Compass in which she argues “that Canadian environmental historians, even as they foreground nature as an historical actor, nevertheless continue to focus their attention and orient their investigations around questions of how human social, cultural, economic, and political power reshaped both nature and human experience in the past.” \n \nThese arguments garnered lots of attention online as environmental historians shared the link to Brady’s article via online social networks and discussed its arguments. Others have now written response articles attempting to answer her question. The discussion has focused on the question of whether environmental history should emphasize materialism and the use of environment as an analytical lens or proceed as a “big tent” that incorporates a wide range of scholarship regardless of methodology. \n \nOn this episode of the podcast, Lisa Brady, Mark Hersey, and Liza Piper discuss this question and further explore whether or not environmental history has lost its way.

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)0.002
metaresearch head score (Gemma)0.005
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.271
Threshold uncertainty score0.540

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0100.004
Scholarly communication0.0090.006
Open science0.0010.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.012
GPT teacher head0.177
Teacher spread0.165 · 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
GenreCommentary

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

Citations0
Published2016
Admission routes1
Has abstractyes

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