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Record W4309074817 · doi:10.1080/14777622.2022.2145191

To Rule the Cosmic Waves: Maritime School of Thought and Space Strategy

2022· article· en· W4309074817 on OpenAlexaboutno aff
Shaun Cameron

Bibliographic record

VenueAstropolitics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityDenialSpace (punctuation)TelecommunicationsPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

A wide range of states support national space agencies. The United States, United Kingdom, Canada, Japan, France, and Australia are developing, or have developed, distinct space divisions within their military. The world is increasingly reliant on the sea for trade and prosperity, but the future will likely shift focus to space with an increasing dependence on space-based technology for a wide range of functions on Earth. Space requires a tailored strategy for states wishing to maintain security beyond the atmosphere and in its links to Earth. The maritime school of thought offers valuable insights for such a strategy. Sea control and denial are important tenets of maritime strategy and are important in space. States wishing to freely navigate, trade, and project power require control over space and the lines of communication upon common routes and orbital domains. Denial of access to key infrastructure, disabling space assets, and interfering with information exchange are an important feature of strategy. Control and denial can be accomplished with a focus on strategic geography around launch sites, and access to orbital domains and lines of communication.

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)0.004
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.024
Scholarly communication0.0120.013
Open science0.0010.004
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0090.002

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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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