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Record W4412052638 · doi:10.70064/mt.v9i1.1168

Pulp to Plutonium

2025· article· en· W4412052638 on OpenAlexaff
Jeremy Packer, Joshua Reeves

Bibliographic record

VenueMedia theory. · 2025
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPlutoniumEnvironmental scienceRadiochemistryChemistry

Abstract

fetched live from OpenAlex

This essay argues that media systems are not passive instruments of military power but active infrastructures that shape how war is conceived, executed, and sustained. Building on Harold Innis’s staples theory and the materialist traditions in media scholarship, we analyze three case studies—the U.S. Civil War, World War I, and the ongoing conflict over rare-earth minerals in the Democratic Republic of Congo—to demonstrate how media-specific demands produce new regimes of logistics, extraction, and violence. In each historical moment, war is not simply conducted through media but organized around it: paper shortages in the 1860s tied to cotton blockades redefined print media as both resource and battleground; telegraphic entanglements during WWI transformed cable infrastructure into a target and tactical medium; and today’s digital economies sustain conflict through their dependence on minerals sourced from war-torn regions. Rather than treating media as ancillary to strategy, we position them as infrastructural cores of military operations. Media circuits demand raw materials, labor infrastructures, and spatial control—linking sovereign power to media logistics in enduring ways. Our analysis reveals that war and media are co-constitutive processes tied together by shared material conditions. From the newspaper to the fiber-optic cable, the terrain of conflict shifts in step with the demands of media technologies. This entwinement renders modern war a struggle not just over territory or ideology but over the infrastructures that make communication—and domination—possible.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score0.997

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)0.0040.000

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 head0.007
GPT teacher head0.257
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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