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Record W2122199361 · doi:10.1111/anti.12173

The Natures of War

2015· article· en· W2122199361 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAntipode · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMateriality (auditing)DialecticFront (military)Relevance (law)BattlefieldHome frontArmed conflictPolitical sciencePolitical economyHistorySociologyWorld War IILawAncient historyGeographyAestheticsPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract “Nature” is more than a resource bank whose riches can trigger armed conflict and finance its depredations; it is also a medium through which military and paramilitary violence is conducted. The militarisation of nature is part of a dialectic in which earthy, vibrant matter shapes the contours of conflict and leaves its marks on the bodies of soldiers who are both vectors and victims of military violence. Three case studies identify some of the central bio‐physical formations that became entangled with armed conflict in the twentieth century: the mud of the Western Front in the First World War, the deserts of North Africa in the Second World War, and the rainforests of Vietnam. Taken together, these reveal vital connections between the materiality and corporeality of modern war and their continued relevance to its contemporary transformations.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.354
Teacher spread0.316 · 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