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Record W1639305740 · doi:10.22230/cjc.2013v38n3a2735

Logistical Media: Fragments from Radar’s Prehistory

2013· article· en· W1639305740 on OpenAlexvenueno aff
Judd A. Case

Bibliographic record

VenueCanadian Journal of Communication · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsPrehistoryRadarFrench hornGestureComputer scienceSociologyTelecommunicationsHistoryMedia studiesArchaeologyArtificial intelligence

Abstract

fetched live from OpenAlex

Fragments from the prehistory of radar are analyzed to advance a notion of logistical media. Logistical media order and arrange people and objects and subtly influence our experiences of space and time (Case, 2010). Logistical media emphasize logistics, feedback, and remote control in communication. They gesture to the work of Innis (1951, 1972), Wiener (1948/1961, 1954), Carey (1988), Mumford (1964), and Virilio (1989, 1994), and to the transmission model of communication. This article considers the torpedo, searchlight, war horn, and death ray logistically and as they prefigure radar. The analysis of other logistical media is suggested.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.005
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.041
GPT teacher head0.290
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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations41
Published2013
Admission routes1
Has abstractyes

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