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Record W4416901372 · doi:10.1515/9781503644793

The Islands and the Stars

2025· book· W4416901372 on OpenAlexaboutno aff
Subodhana Wijeyeratne

Bibliographic record

VenueStanford University Press eBooks · 2025
Typebook
Language
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)CentralityAgency (philosophy)Space programConsolidation (business)Space explorationSpace research

Abstract

fetched live from OpenAlex

The Japan Aerospace Exploration Agency (JAXA) is among the six largest national space agencies in the world, along with China's CNSA, US's NASA, and Russia's Roscosmos. JAXA's budget is more than $1 billion USD—bigger than France or Germany individually, and more than that of Italy, India, Canada, and the UK combined. And yet, Japan's significant contributions have largely been absent in the history of space exploration, and space exploration largely absent in the history of technology in Japan. The Islands and the Stars corrects this conspicuous oversight. Through meticulous archival research in Japanese and anglophone archives, Subodhana Wijeyeratne examines the history of Japan's space exploration efforts over nearly a century.   Wijeyeratne traces the evolution of Japan's space program from its early origins in the 1920s, through the postwar period of rapid technological innovation, to the consolidation of its various institutional elements into JAXA in 2003. He situates Japan's space programs within the broader history of the country's postwar recovery, economic growth, and cultural identity, while also considering their place within global trends in space exploration. Through this narrative, Wijeyeratne not only illuminates Japan's centrality to the global history of science and technology, but also offers insights into the future of global space exploration, emphasizing the importance of diverse voices and perspectives in the quest to understand our place in the cosmos.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.962
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.193
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreOther

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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